Account_Candidate_Attraction
ChatGPTGet EVP data v2 for a specific account Returns Employee Value Proposition scores for the Draup account in the path: an overall EVP index, the number of analysed employee reviews, and pillar and sub-pillar scores with sample reviews. It powers the EVP battlecard comparison on the account profile in the Talent product. Scores are company level by default; passing places such as a country or metro area in response_data.location switches to location-level scores for those places, merged by weighted average. The EVP index is the pillar scores averaged by pillar weight, and zero without data. Request Examples: Cisco EVP data in Pakistan: { "response_data": { "location": { "and": [ { "or": [ [ "Pakistan", "location", false, true ] ] } ] } } }
accounts_customers_summary_v3
ChatGPTGet customer summary for an account Returns three headline metrics about a service provider's customer base, for the company with Draup account id id, each as a card with label, a values array and icon. active_customers is the number of distinct customer companies with at least one active outsourcing engagement in which this company is the vendor; active_workflows is the number of distinct active engagements across those customers. key_customers is a list of [customer name, active engagement count] pairs ranked by engagement count, then name, with three entries by default. Only customers present in Draup's company universe are counted. The key-customer list can be paged with a pagination JSON query parameter (offset, limit); the two counts are unaffected. A company that is not recorded as a vendor in any active engagement returns zero counts and an empty key-customer list.
accounts_financials_get_financials_tabs_v3
ChatGPTGet which financial sections have data for a company Tells you which financial sections hold data for a company, identified by its numeric Draup account id (id), so you can skip calls that would come back empty. Each key is a boolean: statements when income statement, balance sheet or cash-flow figures exist; growth and ratios when ratio data exists or when closing prices for at least two reference dates (now and one, three or five years ago) are available for the company's listed ticker from a third-party stock-data provider; transcripts when quarter-tagged earnings call transcripts exist; conference_transcripts when conference transcripts exist; and holdings when shareholder records exist. announcements is true only when at least one announcement or filing was filed in the last 12 months, even though the announcements endpoint also returns older items. Forecast figures do not count toward availability.
accounts_financials_revenue_by_region_post_v3
ChatGPTGet account revenue by region Returns the geographic revenue split reported by a public company, identified by its Draup account id (id). The request body (for example {"widget": "revenue_by_region"}) does not change the result. data maps each region name exactly as the company reports it (segment names vary by company) to a list whose first entry covers the latest fiscal year and second entry the prior fiscal year. Each entry gives amount in millions, currency and year; the latest-year percentage is the region's share of the company's total reported annual revenue. year echoes the latest fiscal year (the company's most recent year of reported annual revenue), headerSuffix names the currency and unit, and a footnote explains the figures. Regions with no revenue in the latest year are omitted. Private companies, or companies without regional disclosures, return {"data": {}, "year": null}, and data is also empty when total annual revenue for that year is unavailable. Request Examples: Revenue by region for account 893342625: { "widget": "revenue_by_region" } Revenue by region for account 17396: { "widget": "revenue_by_region" }
accounts_get_skills_architecture_v3
ChatGPTGet skills architecture roles for an account Returns the skills architecture of the company given by id, derived from its job postings: one entry per job role with role_name, the role's job_family and job_occupation from the role taxonomy, and the most frequent core_skills, soft_skills, digital_products, job_title_lemmatized titles and sub_workloads (work activities) found in that role's postings, plus total_count, the number of distinct roles. Roles are ranked by posting volume (up to 1,000) and paged with pagination.offset/limit (default 10); limit also caps how many values each list carries. response_data filters the underlying postings and accepts job_occupations, job_families, core_skills, workloads, business_functions, job_titles, multiple_locations and accounts; other keys return HTTP 400. The company scope always comes from the path id and overrides any accounts value. Request Examples: No filters, first page with default pagination: { "pagination": { "limit": 25, "offset": 0 } } Filter by Software AND Mathematics occupation and Software & Technology Management family: { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "job_families": { "or": [ "software & technology management" ] }, "job_occupations": { "or": [ "software and mathematics" ] } } } Filter by Sales & Marketing occupation: { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "job_occupations": { "or": [ "sales & marketing" ] } } }
accounts_hiring_demand_category_v3
ChatGPTGet hiring demand category metrics for an account Ranks the most in-demand values of one hiring dimension for an account, from its job postings over the last 12 months. Pick the dimension with filter_name (query or body): workloads, core_skills, soft_skills, job_title, business_functions, certification, education, job_type or experience; others return HTTP 400. Each result item holds the value (keyed by the dimension name), job_postings, a 13-month last_12_months_trend of monthly counts (ym as MM-YYYY), and change_compared_to_previous_12_months, set to "Trending Up" or "Declining" only when quarterly counts rise or fall in every quarter. count is the number of distinct values. experience instead returns a histogram of minimum required years. Body demand_type ("All" by default, "Trending Up" or "Declining") keeps matching trends; pagination pages results (default 10). response_data accepts business_functions, workloads, core_skills, job_titles and multiple_locations (any-of; other keys return HTTP 400). Request Examples: Demand by workloads with simple location and business function filters: { "filters": { "locations": [ "global" ], "business_functions": [ "IT" ] }, "demand_type": "All", "filter_name": "workloads" } Education breakdown filtered by global location with pagination: { "pagination": { "limit": 10, "offset": 0, "sortBy": "job_posting", "sortType": "DESC" }, "demand_type": "All", "filter_name": "education", "response_data": { "multiple_locations": { "or": [ "global" ] } } } Core skills breakdown filtered by location and ER&D business function: { "pagination": { "limit": 10, "offset": 0, "sortBy": "job_posting", "sortType": "DESC" }, "demand_type": "All", "filter_name": "core_skills", "response_data": { "business_functions": { "or": [ "ER&D" ] }, "multiple_locations": { "or": [ "global" ] } } }
accounts_hiring_timeline_v3
ChatGPTGet hiring timeline for an account Returns the month-by-month count of an account's job postings over a rolling 12-month window ending today. hiring_timeline lists the complete calendar months (year, month, job_count); partial_months_hiring_timeline holds the incomplete months at the window's edges, with start_date on the first and end_date (today) on the current month. avg and stddev are the mean and standard deviation of the complete-month counts, and plot_points gives five reference levels: mean minus two and one standard deviations, mean, and mean plus one and two. Entries can be null when the lower levels would fall below zero. Optional response_data narrows the postings: business_functions, workloads, core_skills, job_titles and multiple_locations ("global" means all locations). Values within a key match any-of, not exclusions are ignored, and any other key returns HTTP 400. The same lists may also be sent as filters entries; response_data takes precedence. Request Examples: Filter by global multiple_locations only: { "filters": { "trend": false }, "response_data": { "multiple_locations": { "or": [ "global" ] } } } Filter by global location and ER&D business function: { "filters": { "trend": false }, "response_data": { "business_functions": { "or": [ "ER&D" ] }, "multiple_locations": { "or": [ "global" ] } } } Filter by locations, business functions, workloads and sort by job_posting: { "filters": { "trend": false }, "pagination": { "sortBy": "job_posting", "sortType": "DESC" }, "response_data": { "workloads": { "or": [ "Artificial Intelligence & Data Science" ] }, "business_functions": { "or": [ "ER&D", "Sales & Marketing" ] }, "multiple_locations": { "or": [ "global" ] } } }
accounts_talent_flow_insights_companies_v3
ChatGPTGet talent flow insights for companies Shows which companies the company given by id gains talent from and loses talent to over filters.monthly_time_frame (min/max as MM-DD-YYYY; by default the 12 months ending with the month three months before the current one). Built from professional profiles and employment histories: per company, hiring counts professionals who joined the target in the window from it (previous employer), attrition those who left the target in the window for it (next employer), and net_gain_loss is hiring minus attrition. req_type and workforce_type are required. workforce_type all returns table_data plus total_count, with account_id on known companies; is_parent/is_child mark the target's parent and subsidiaries. Rows sort by pagination.sortBy (net_gain_loss, hiring, attrition, key; absoluteSort ranks by total movement) and page by limit/offset (default 10). Other types return ranked {key, value, additional_data} lists. response_data accepts only job_families, locations, competitors and projects; any other key returns HTTP 400. Request Examples: Table view for all companies over a time frame without location or job family filters: { "filters": { "monthly_time_frame": { "max": "07-31-2026", "min": "08-01-2025" } }, "req_type": "table", "pagination": { "limit": 500, "offset": 0, "sortBy": "net_gain_loss", "sortType": "desc", "absoluteSort": true }, "workforce_type": "all" } Graph view filtered by a specific location: { "filters": { "monthly_time_frame": { "max": "07-31-2026", "min": "08-01-2025" } }, "req_type": "graph", "pagination": { "offset": 0 }, "response_data": { "locations": { "or": [ "United Kingdom" ] } }, "workforce_type": "net_gain_loss" } Graph view filtered by location and job family: { "filters": { "monthly_time_frame": { "max": "07-31-2026", "min": "08-01-2025" } }, "req_type": "graph", "pagination": { "offset": 0 }, "response_data": { "locations": { "or": [ "United Kingdom" ] }, "job_families": { "or": [ "Software & Technology Management" ] } }, "workforce_type": "net_gain_loss" }
accounts_talent_flow_insights_locations_v3
ChatGPTGet talent flow location insights for an account Breaks down talent movement at the company given by id by the metro area (MSA) where professionals worked there, over filters.monthly_time_frame (min/max as MM-DD-YYYY; by default the 12 months ending with the month three months before the current one). Built from professional profiles and their employment histories: hiring counts tenures at the company that started in the window, attrition tenures that ended in it, and net_gain_loss is hiring minus attrition. req_type and workforce_type are required. workforce_type all returns table_data rows plus total_count, sorted by pagination.sortBy (net_gain_loss, hiring, attrition or key; absoluteSort with net_gain_loss ranks by total movement) and paged by limit/offset (default 10). hiring or attrition return a ranked {key, value} list with latitude, longitude and country; net_gain_loss returns net gainers then net losers. response_data accepts only job_families, locations, competitors and projects; any other key returns HTTP 400. filters.work_experience narrows by years of experience. Request Examples: Table view, all workforce, time-bounded, no entity filters: { "filters": { "monthly_time_frame": { "max": "07-31-2026", "min": "08-01-2025" } }, "req_type": "table", "pagination": { "limit": 500, "offset": 0, "sortBy": "net_gain_loss", "sortType": "desc", "absoluteSort": true }, "workforce_type": "all" } Graph view, net gain/loss, filtered to a specific country location: { "filters": { "monthly_time_frame": { "max": "07-31-2026", "min": "08-01-2025" } }, "req_type": "graph", "pagination": { "offset": 0 }, "response_data": { "locations": { "or": [ "United Kingdom" ] } }, "workforce_type": "net_gain_loss" } Graph view, net gain/loss, filtered by country and two job families: { "filters": { "monthly_time_frame": { "max": "07-31-2026", "min": "08-01-2025" } }, "req_type": "graph", "pagination": { "offset": 0 }, "response_data": { "locations": { "or": [ "United Kingdom" ] }, "job_families": { "or": [ "Software & Technology Management", "Systems Management & Engineering" ] } }, "workforce_type": "net_gain_loss" }
accounts_talent_flow_top_metrics_v3
ChatGPTGet top talent flow metric for an account Returns one headline talent-flow figure for the company given by id as {value, percent}, selected by the required metric: hiring, attrition or workforce_growth (anything else returns HTTP 400). Over filters.monthly_time_frame (min/max as MM-DD-YYYY; by default the 12 months ending with the month three months before the current one), hiring counts professionals who joined the company and attrition those who left; their percent is that count divided by the average of current and previous workforce, times 100. Workforce is the number of profiled professionals employed at the end of the window, and previous workforce the same at the end of the preceding period of equal length. For workforce_growth, value is the workforce change and percent the percentage change; a zero denominator yields 0 for both. response_data accepts only job_families, locations, competitors and projects; any other key returns HTTP 400. filters.work_experience narrows by years of experience. Request Examples: Hiring metric with only time frame: { "metric": "hiring", "filters": { "monthly_time_frame": { "max": "07-31-2026", "min": "08-01-2025" } } } Workforce growth filtered by United Kingdom location: { "metric": "workforce_growth", "filters": { "monthly_time_frame": { "max": "07-31-2026", "min": "08-01-2025" } }, "response_data": { "locations": { "or": [ "United Kingdom" ] } } } Hiring filtered by SF Bay Area and selected companies: { "metric": "hiring", "filters": { "monthly_time_frame": { "max": "07-31-2026", "min": "08-01-2025" } }, "response_data": { "locations": { "or": [ "San Francisco Bay Area, United States" ] }, "competitors": { "or": [ "Intel Corporation", "Apple Inc." ] } } }
accounts_talent_flow_workforce_trends_v3
ChatGPTGet workforce trends for an account Returns a month-by-month talent-flow series for the company given by id across filters.monthly_time_frame (min/max as MM-DD-YYYY; by default the 12 months ending with the month three months before the current one), one entry per month keyed like Aug 2025. Counts come from professional profiles and their employment histories: hiring is tenures at the company that started in the month, attrition tenures that ended in it, net_gain_loss their difference, and total_workforce the number of profiled professionals employed there at the end of the month. req_type and workforce_type are required. req_type table always returns all four measures per month; otherwise workforce_type hiring, attrition, total_workforce or net_gain_loss returns {key, value, additional_data} per month. Months are chronological unless pagination.sortBy/sortType is given. response_data accepts only job_families, locations, competitors and projects; any other key returns HTTP 400. filters.work_experience narrows by years of experience. Request Examples: Table view for all workforce without entity filters: { "filters": { "monthly_time_frame": { "max": "07-31-2026", "min": "08-01-2025" } }, "req_type": "table", "workforce_type": "all" } Graph view for total workforce filtered by location: { "filters": { "monthly_time_frame": { "max": "07-31-2026", "min": "08-01-2025" } }, "req_type": "graph", "response_data": { "locations": { "or": [ "United Kingdom" ] } }, "workforce_type": "total_workforce" } Graph view for total workforce filtered by location, job families, and companies: { "filters": { "monthly_time_frame": { "max": "07-31-2026", "min": "08-01-2025" } }, "req_type": "graph", "response_data": { "locations": { "or": [ "San Francisco Bay Area, United States" ] }, "competitors": { "or": [ "Intel Corporation", "Apple Inc." ] }, "job_families": { "or": [ "Software & Technology Management", "Systems Management & Engineering" ] } }, "workforce_type": "total_workforce" }
base_pay_compare_roles
ChatGPTCompare base pay for multiple job roles Compares the base pay for specified job roles using filters such as job roles, job location, years of experience, and job country. Returns detailed pay statistics for each role. Request Examples: Compare Content Producer and Content Director in Greater Los Angeles Area: { "filters": { "job_roles": [ "Content Producer", "Content Director" ], "job_location": [ "Greater Los Angeles Area, United States" ] } } Compare Content Director and Content Producer with years of experience filter: { "filters": { "job_roles": [ "Content Director", "Content Producer" ], "job_location": [ "Greater Los Angeles Area, United States" ], "years_of_experience": { "max": 20, "min": 10 } } } Compare multiple healthcare roles in United States of America: { "filters": { "job_roles": [ "Physician", "Nurse", "Pharmacist", "Therapist", "Physician Assistant", "Dentist", "Clinical Social Worker", "Psychologist" ], "job_country": [ "United States of America" ] } }
build_company_filters_v3
ChatGPTTurn a company search query into company directory filters Interprets a natural-language search query about companies and returns structured filters for the Draup company directory: boolean_response, an entity-keyed tree of or/and/not value lists (for example {"companies": {"or": ["Nvidia Corporation"]}}) to send as response_data to get_universe_companies_v3; synon_list with the Draup values each term was matched or expanded to; range filters such as revenue, employee count, funding amount or year established; a suggested pagination sort and view_name; and an identifier. Use it when you need company-search filter values from a free-text request. An AI model interprets the query together with today's date, the directory's filter vocabulary and the sortable columns available for the caller's product. Terms that do not map to a usable filter come back as free-text keywords. Only current_input is interpreted; the other body fields are accepted but ignored. When the query cannot be interpreted the call still returns HTTP 200, with is_valid false and an error_message instead of filters. Request Examples: Minimal body with only free-text input: { "current_input": "semiconductor companies in Bangalore" } Parse input with project context and different sort field: { "view_name": "Opportunities", "pagination": { "limit": 25, "offset": 0, "sortBy": "exec_movement_flag", "sortType": "DESC nulls last" }, "project_id": 267402, "current_input": "google" } Parse company name for Opportunities view with scoring sort: { "view_name": "Opportunities", "pagination": { "limit": 25, "offset": 0, "sortBy": "talent_oi_score", "sortType": "DESC nulls last" }, "current_input": "Nvidia Corporation" }
build_news_filters_v3
ChatGPTTurn a news search query into Signals filters Interprets a natural-language search query about company news and returns structured Signals filters: a rephrased search phrase, plus any companies, industry verticals, signal categories and saved project lists it recognises, a capture-date range when the query implies one, and synonym records for the matched company names. Use it when you need Signals filter values from a free-text request, then send boolean_response as response_data (and filters as filters) to a Signals search tool such as get_signal_news_v3. An AI model interprets the query, so the same query can give slightly different filters, and only entities enabled for the caller's Signals search are returned. When the query cannot be interpreted, the response has is_valid false and an optional error_message, and carries no filters. Request Examples: Topic query: { "current_input": "labor market news" } Query naming a signal category and a company: { "current_input": "recent deals and partnership news about Microsoft" }
customers_deals
ChatGPTGet Customers Deals for Account Profile Returns a service-provider snapshot of the Draup account in the path, built from the active outsourcing deals where it is the vendor: its top customers, the verticals of the customers it serves, its main delivery locations and the workloads it delivers. It powers the Customers and Deals widget on the account profile of IT, engineering and professional services firms. Data exists only when the account's primary vertical is IT Services, Product Engineering Services or Professional Services; for any other company all four parts come back empty. Each part holds at most three entries: customers ranked by the number of active deals with this vendor, counting only customers visible to the caller's product, customer verticals ranked by the number of distinct customers, and delivery locations and workloads ranked by the number of deals. A deal counts as active when it is not flagged inactive and has no end date or one in the future. No filters apply. Request Examples: Basic request with no filters: { "widget": "customers_deals" }
customers_deals_v3
ChatGPTGet a service provider's top customers, customer verticals, delivery locations and workloads Returns a snapshot of a service provider's outsourcing business, built from the active outsourcing deals in which the company is the vendor: its top customers, the verticals those customers belong to, its main delivery locations and the workloads it delivers. Use it to see who an IT services, engineering services or professional services firm works for and what it delivers. Data exists only when the company's primary vertical is IT Services, Product Engineering Services or Professional Services; for any other company, or a service provider with no active deals, every list is null or left out. Each list holds up to the top three entries: customers by number of active deals with this vendor, customer verticals by number of distinct customers, and delivery locations and workloads by number of deals. Only deals whose customer is visible in the caller's product are counted, for all four lists. A list is null or left out when there is no data for it. A deal is active when it is not flagged inactive and has no end date or one in the future. Each customer's account_id is a Draup account ID. The endpoint takes no filters. An unknown account ID, or one the caller cannot access, returns an empty response with no result.
demographics_data
ChatGPTGet Demographics Data Retrieves demographic, labor, and business environment data for specified job roles and locations. Request Examples: Filter by job_role and job_country: { "filters": { "job_role": "Software AND Mathematics", "job_country": [ "Vietnam" ] } } Filter by job_role and job_location: { "filters": { "job_role": "Data Scientist", "job_location": [ "Bengaluru Area, India" ] } }
ecosystem_get_organization_decreasing_workforce
ChatGPTGet organization data with decreasing workforce for a vertical Returns a list of organizations within the specified vertical/industry that have experienced a decrease in workforce, along with attrition percentages and percentile statistics. Request Examples: Automotive vertical example: { "analysis_entity": "Automotive" }
ecosystem_get_organization_increasing_workforce
ChatGPTGet organization data for increasing workforce by vertical Retrieves a list of organizations within a specified vertical (analysis_entity) that are experiencing an increasing workforce trend. The response includes workforce counts, attrition percentages, and percentile thresholds (33rd and 67th) to help classify organizations into high, medium, or low categories based on attrition. Request Examples: Automotive vertical example: { "analysis_entity": "Automotive" }
ecosystem_get_vertical_it_spend
ChatGPTGet IT Spend Top Metrics Returns the current value and change percentage of IT spend for a specified analysis entity (vertical). Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }
ecosystem_get_vertical_key_priorities
ChatGPTGet vertical key priorities Fetches a list of key priorities for a specific vertical or analysis entity. The response includes detailed descriptions, functional categories, and a relevance flag for each priority item. Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }
ecosystem_get_vertical_organization_top_employers
ChatGPTGet Top Employers for an Analysis Entity Returns a list of top employer organizations for the specified analysis entity (such as a vertical or industry). Each employer includes its account ID, name, logo URL, and employee count. Also returns percentile information for employee counts. Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }
ecosystem_get_vertical_organization_top_startups
ChatGPTGet Top Startups Organization Data Returns a list of top startups for a given analysis entity, with optional filters for sub-verticals or locations. Request Examples: No filters: { "analysis_entity": "Product Engineering Services" } Filter by locations: { "response_data": { "locations": { "AND": [ { "OR": [ [ "Greater Los Angeles Area, United States", "locations", false, true ] ] } ] } }, "analysis_entity": "Aerospace" } Filter by sub-verticals: { "response_data": { "sub_verticals": { "AND": [ { "OR": [ [ "Oil & Gas Upstream", "sub_verticals", false, true ] ] } ] } }, "analysis_entity": "Energy & Utilities" }
ecosystem_get_vertical_outsourcing_customers
ChatGPTGet Outsourcing Customers by Vertical Retrieves a list of outsourcing customers for the specified vertical (analysis_entity). The response includes company details and percentile information. Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }
ecosystem_get_vertical_outsourcing_vendors
ChatGPTGet Outsourcing Vendors by Vertical Retrieves a list of outsourcing vendors for the specified vertical (analysis_entity). The response includes vendor details and percentile information. Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }
ecosystem_get_vertical_outsourcing_workloads
ChatGPTGet Outsourcing Workloads by Analysis Entity Returns a list of outsourcing workloads and their sizes for a specified analysis entity (vertical/industry). Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }
ecosystem_get_vertical_revenue
ChatGPTGet Top Metrics Revenue Fetches the top metrics revenue for a specified analysis entity (vertical). Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }
ecosystem_get_vertical_rnd_spend
ChatGPTGet Top Metrics R&D Spend Returns the current value and change percentage of R&D spend for a given analysis entity (vertical). Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }
ecosystem_get_vertical_techstack_growing
ChatGPTGet Growing Tech Stack Products Retrieves a list of growing technology stack products for a specified analysis entity (vertical/industry). The response includes product details and percentile statistics. Request Examples: Automotive vertical example: { "analysis_entity": "Automotive" }
ecosystem_get_vertical_techstack_popular
ChatGPTGet Popular Tech Stack Products Retrieves a list of popular technology stack products for a specified analysis entity (vertical/industry). The response includes product details and percentile statistics. Request Examples: Automotive vertical example: { "analysis_entity": "Automotive" }
get_account_acquisitions
ChatGPTGet Partnerships and Mergers for an Account Returns the acquisitions made by the account in the path: a table of acquired companies, a yearly acquisition timeline and acquisition counts and deal value by country. It powers the acquisitions table, timeline and map widgets of the account Investments and Acquisitions (Partnerships) tab. Acquisitions can be limited to a recent time period, such as the last one or three years; with no period there is no date limit, though the timeline then covers the last five years. Each acquisition shows its date, acquired company, acquired workloads, primary acquisition intent, location, deal size in US dollars formatted in thousands, millions or billions, and the acquiree's Draup account when it has one, newest first, with every row returned. The timeline counts acquisitions per year, newest first, and the map gives counts and summed raw US dollar deal size per country, counting only acquisitions whose location maps to a Draup location. Request Examples: No filters: null Empty time period: null Filter by time period: { "filters": { "time_period": [ "Maximum" ] } }
get_account_details
ChatGPTGet About Profile for Account Returns the company profile of the Draup account in the path for the About widget at the top of the Universe account profile page: the about text, primary vertical, verticals and sub-verticals, headquarters and address, employee count, vision, mission, founding year, ownership type, links, parent company and Opportunity Index score. The widget always describes that single account and takes no filters. The Opportunity Index score is shown with two decimals and is a weighted sum of index components whose weights are normalised to total 10. Parent company details are filled only when the parent is itself a Draup account. Sales and Talent build the score from different components, with Sales weighing outsourcing, service-provider partners, globalization and investments and Talent weighing headcount, M&A, layoff signals and R&D workforce, so the same account can score differently. An account not visible to the caller's product returns an empty result. Request Examples: Basic About Widget Request: null
get_account_details_v3
ChatGPTGet a company's profile overview Returns the profile overview of one company tracked by Draup: name, business description, primary vertical, verticals and sub-verticals, headquarters and HQ street address, employee count, year established, ownership type (Public or Private), vision and mission statements, website and social media links, parent company, and the Draup Opportunity Index score. Use it for a quick factual summary of a company before deeper research. oi_score is Draup's Talent Opportunity Index, a 0-10 score rounded to two decimals that weighs total headcount, R&D workforce, job postings, layoff signals, revenue, revenue growth, executive movement and mergers and acquisitions equally; it is null for companies without an index. Parent company fields are filled only when the parent is itself a Draup account. Fields without data are null or left out. The endpoint takes no filters. An unknown account ID, or one the caller cannot access, returns an empty response with no result.
get_account_financials
ChatGPTRetrieve financial information for a specific account Returns the latest financial snapshot of the Draup account in the path for the Financials widget of the Universe account profile: revenue, IT spend, R&D spend and EBITDA with their growth figures, the financial year they refer to, the ownership type, and private funding details such as number of rounds, total raised, last round, valuation and latest investor. The four headline figures are expressed in millions alongside a currency code and that currency's conversion rate to US dollars, and each is left empty when the figure or the rate is missing. The year shown is the latest financial year with revenue data. Total funding is the sum of all round amounts, and the last round's date, amount and company valuation are given. The funding details are empty for accounts with no recorded funding rounds, which is typical of public companies. No filters apply, and an account not visible to the caller's product returns an empty result.
get_account_financials_v3
ChatGPTGet a company's latest financial snapshot Returns the latest financial snapshot of one company tracked by Draup: revenue, IT spend, R&D spend and EBITDA with their year-over-year growth, the financial year they refer to, the ownership type, and private funding details (number of rounds, total raised, date and amount of the last round, latest valuation, latest investor). Use it to size a company or check its recent financial trajectory. The four headline figures are in millions of the company's reporting currency, named in each figure's currency field. avg_conversion_rate is the US-dollar value of one unit of that currency, so multiply by it to get US dollars. A figure's value is null or left out when the figure or the rate is unavailable. Growth fields are percentages versus the previous year. concerned_year is the latest financial year with revenue data. Funding amounts are absolute US-dollar values, not millions, and funding fields are null or left out for companies with no recorded funding rounds, which is typical of public companies. The result holds at most one record. The endpoint takes no filters. An unknown account ID, or one the caller cannot access, returns an empty response with no result.
get_account_hiring_timeline
ChatGPTGet hiring timeline for an account Returns the monthly count of job postings published by the Draup account in the path over the trailing 12 months, with the average, standard deviation and band values behind the hiring timeline chart on the account's Hiring view. It helps spot hiring spikes or slowdowns. Counts can be narrowed by skills, workloads, business functions, job titles and location. The window runs from the same day last year up to yesterday. Complete calendar months, usually 11, are listed with zero where there were no postings, and the partial first and current months come separately with their start or end dates. The average and sample standard deviation cover the complete months, and the bands mark one and two deviations either side of the average, left empty when the average or deviation is zero or a lower band would fall below zero. An account with no postings still returns every month at zero. Request Examples: Sample body payload 1: { "filters": { "trend": false, "locations": [ "global" ] } } Sample body payload 2: { "filters": { "trend": false, "locations": [ "global" ] }, "pagination": { "sortBy": "job_posting", "sortType": "DESC" } }
get_account_hiring_trends
ChatGPTFetch hiring demand data by category Ranks the values of one job posting attribute, such as skills, job titles, workloads, business functions, education, certifications, job type or experience, across the job postings the Draup account in the path published in the last 12 months. It powers the Hiring demand widgets of the account profile. Results can be narrowed by skills, workloads, business functions, job titles and location, or limited to values labelled Trending Up or Declining. Each value carries its 12-month posting count, a 13-month trend whose first and last months are partial, and a label comparing quarterly totals inside the window. Values are ranked by posting count, most first by default, ten per page; only the top 1,000 are analysed and the total number of values is approximate. The experience attribute instead returns postings by required years of experience with a standard deviation and an availability percentage. When no postings match, the list is empty. Request Examples: Top 10 core skills by job postings: { "pagination": { "limit": 10, "offset": 0, "sortBy": "job_posting", "sortType": "DESC" }, "demand_type": "All" }
get_account_id
ChatGPTFind a company's Draup account ID Looks up companies by name or website in Draup's company directory and returns each match with its Draup account id (id, the id that account tools such as get_account_details_v3 take), company name (key), logo, a 0 to 1 match score and whether the match was AI-suggested. Use it first whenever you have a company name or website and need its account id. A search term that looks like a website domain (for example microsoft.com) is matched against every known company web address, including subsidiary and brand domains, and returns those companies with score 1, up to ten. Otherwise the name goes to Draup's company name-matching service, which keeps companies scoring at least 0.5 and returns at most five, highest score first (direct matches before AI-suggested ones at the same score). Send type as "universe". Results are empty when nothing matches or the caller's plan does not include company search. Request Examples: Look up by website: { "type": "universe", "search_key": "microsoft.com" } Look up Microsoft: { "type": "universe", "search_key": "microsoft" }
get_account_investments
ChatGPTGet account investments Returns the investments the account in the path has made in startups and other companies: a table of individual deals, a yearly investment timeline and deal counts by funding stage. It powers the investments table, timeline and by-stage widgets of the account Investments and Acquisitions (Partnerships) tab. Deals can be narrowed by investment type, such as Venture, Grant or Pre Seed, and by a recent time period such as the last one or three years; with no period there is no date limit, though the timeline then covers the last five years. Deals without a funding round can be dropped from the stage counts. Each deal shows its date, invested company, workloads, type, locations, amount formatted in thousands, millions or billions, round, partner accounts, the investee's Draup account and investment intent, newest first, with every deal returned. The timeline gives deal counts and summed amounts in millions per year, added across currencies. Request Examples: No filters: null Empty time period: null Filter by time period: { "filters": { "time_period": [ "Maximum" ] } }
get_account_key_locations
ChatGPTGet key location insights for a business function Returns the key locations of the Draup account in the path for the Location Insights map: for each metro area with sites or recent job postings, the site workforce, last 12 months of postings, a growth index, site tags and coordinates, plus legend thresholds for workforce and growth. Results can be limited to one business function, restricting sites and postings, and to sites with chosen tags, whose metro areas then bound the posting counts. Without a business function an area can appear once per function. Locations rank by workforce, then postings, ten by default. The growth index is postings per site employee, zero without postings and empty without workforce; areas with no workforce but more than four postings are tagged New Site. Workforce thresholds are the 33rd and 66th percentiles of non-zero sizes, and growth thresholds are the mean growth index minus and plus one standard deviation. With no locations the list is empty. Request Examples: Sample request with business_function IT: { "pagination": { "limit": 50 }, "business_function": "IT" }
get_account_key_solution_offerings
ChatGPTGet Key Solution Offerings for an Account Profile Returns up to 20 technology products developed by the Draup account in the path, meaning products whose developer company is this account, ranked by how many companies use them. It powers the Key Solution Offerings widget on the Universe account profile and shows which of a vendor's products are most widely adopted. Each product comes with its Draup product id, name, logo and the number of companies whose tech stack includes it, and the list is sorted by that adoption count, highest first. The result is empty when the account develops no tracked product, which is the common case for companies that are not software vendors. No filters apply, and an account not visible to the caller's product also returns an empty result. Request Examples: Basic request with empty filters: null
get_account_key_solution_offerings_v3
ChatGPTGet the most widely used technology products a company develops Returns up to 20 technology products developed by the company, ranked by how many companies use them. Use it to see which of a software or technology vendor's products are most widely adopted. Each product has its Draup product ID, name, logo URL and accounts_using, the number of companies whose tech stack includes it; products are sorted by accounts_using, highest first. The result is empty when the company develops no tracked product, which is common for companies that are not technology vendors. The endpoint takes no filters. An unknown account ID, or one the caller cannot access, returns an empty response with no result.
get_account_priorities
ChatGPTGet Account Priorities Fetches account priorities for a given Draup account. Allows filtering by business function, usecase, workloads, and technology area. Request Examples: No filters applied, with pagination limit 10.: { "pagination": { "limit": 10 } } Filter by business function, usecase, workloads, and technology area with pagination limit: { "pagination": { "limit": 10 }, "response_data": { "usecase": { "AND": [ { "OR": [ [ "AI-optimized Data Center Infrastructure", "usecase", false, true ] ] } ] }, "workloads": { "AND": [ { "OR": [ [ "Artificial Intelligence & Data Science", "workloads", false, true ] ] } ] }, "technology_area": { "AND": [ { "OR": [ [ "Artificial Intelligence", "technology_area", false, true ] ] } ] }, "business_function": { "AND": [ { "OR": [ [ "ER&D", "business_function", false, true ] ] } ] } } } Filter by business function: { "response_data": { "business_function": { "AND": [ { "OR": [ [ "ER&D", "business_function", false, true ] ] } ] } } } Filter by business function and usecase: { "response_data": { "usecase": { "AND": [ { "OR": [ [ "AI-optimized Data Center Infrastructure", "usecase", false, true ] ] } ] }, "business_function": { "AND": [ { "OR": [ [ "ER&D", "business_function", false, true ] ] } ] } } } Filter by business function, usecase, and workloads with pagination limit.: { "pagination": { "limit": 10 }, "response_data": { "usecase": { "AND": [ { "OR": [ [ "AI-optimized Data Center Infrastructure", "usecase", false, true ] ] } ] }, "workloads": { "AND": [ { "OR": [ [ "Artificial Intelligence & Data Science", "workloads", false, true ] ] } ] }, "business_function": { "AND": [ { "OR": [ [ "ER&D", "business_function", false, true ] ] } ] } } }
get_account_priorities_v3
ChatGPTGet a company's strategic priorities Returns the strategic business priorities Draup has identified for one company. Each priority includes its name and narrative description, business function, the functional workloads it involves, the use cases it applies to (with each use case's description and technology areas), its source (earnings call Transcript and/or news Signal) with the fiscal quarter or publication month, up to six of the company's tech stack products whose workloads overlap the priority plus the total number of overlapping products, and up to six service providers with active outsourcing engagements on those workloads. Use it to learn what a company is investing in or trying to achieve, and which tools and vendors are linked to each initiative. {id} is the company's Draup account ID, as returned by get_account_id or get_universe_companies_v3. Narrow the list with response_data (business_functions, workloads, usecases, technology_areas) or with search_key, which matches part of the priority name. Earnings call (Transcript) priorities come first, latest fiscal quarter first, followed by news (Signal) priorities, latest month first, so an older transcript priority is listed before a recent signal priority. Results come 50 per page by default; use pagination.limit and pagination.offset for more. Fields with no value are left out, and is_competitor is always false for API calls. Request Examples: ER&D priorities: { "response_data": { "business_functions": { "or": [ "ER&D" ] } } } Priorities whose name contains 'service', excluding Legal: { "search_key": "service", "response_data": { "business_functions": { "not": [ "Legal" ] } } } Priorities with AI use cases, first 10: { "pagination": { "limit": 10, "offset": 0 }, "response_data": { "technology_areas": { "or": [ "Artificial Intelligence" ] } } }
get_account_tech_stack_products
ChatGPTRetrieve tech stack products/tools used for an account Fetches a list of tech stack products for the specified account. Supports advanced filtering using logical operators (AND/OR) on sub-categories, workloads, developer companies, and categories. Request Examples: No filters: { "pagination": { "limit": 10 } } Filter by workloads: { "response_data": { "workloads": { "AND": [ { "OR": [ [ "Software Testing", "workloads", false, true ] ] } ] } } } Filter by categories: { "pagination": { "limit": 10 }, "response_data": { "categories": { "AND": [ { "OR": [ [ "Human Capital Management Software (HCM)", "categories", false, true ] ] } ] } } } Filter by sub_categories: { "response_data": { "sub_categories": { "AND": [ { "OR": [ [ "Okta Integration Network Software", "sub_categories", false, true ] ] } ] } } } Filter by developer_companies: { "response_data": { "developer_companies": { "AND": [ { "OR": [ [ "Workday, Inc.", "developer_companies", false, true ] ] } ] } } }
get_account_tech_stack_products_v3
ChatGPTGet the technology products a company uses Returns the software and technology products Draup has detected in one company's tech stack, one row per product: product name and ID, tech stack category, G2 sub-category, developer company, the workloads the product supports, the countries where its use was evidenced (which can include Remote or Hybrid), first and last evidence dates, a usage index (High, Medium or Low; rarely NA) and a detection confidence score from 0 to 1. Products Draup no longer detects are still listed but have no usage index; use last_evidence_date to judge how current a product is. Rows are sorted by G2 sub-category, then product name. Use it to find which tools and vendors a company uses, or whether it uses a given product or vendor. {id} is the company's Draup account ID, as returned by get_account_id or get_universe_companies_v3. Narrow the list with response_data (tech_stack_categories, tech_stack_sub_categories, tech_stack_developer_companies, workloads, countries). Each product has one category and one sub-category, so use only or / not for those two; "and" on them returns an error. Results come 50 per page by default; use pagination.limit and pagination.offset for more, since large companies can have thousands of products. Fields with no value are left out, and is_competitor is always false for API calls. Request Examples: Security software used in the United States, first 20: { "pagination": { "limit": 20, "offset": 0 }, "response_data": { "countries": { "or": [ "United States of America" ] }, "tech_stack_categories": { "or": [ "Security Software" ] } } } Cybersecurity products not developed by Microsoft: { "response_data": { "workloads": { "or": [ "Cybersecurity" ] }, "tech_stack_developer_companies": { "not": [ "Microsoft" ] } } } Products developed by Microsoft: { "response_data": { "tech_stack_developer_companies": { "or": [ "Microsoft" ] } } }
get_account_top_outsourced_workloads
ChatGPTGet a company's most-outsourced workloads Returns the five workloads a company outsources most, ranked by how many of its active outsourcing deals cover each workload. Use it to see where a company relies most on external service providers. {id} is the company's Draup account id, as returned by get_account_id or get_universe_companies_v3. Only deals that name at least one workload, are flagged active, have no end date or one in the future, and have a vendor that is itself a Draup account are counted. Workload names come from Draup's workload taxonomy, such as Customer Service & Support or Software Testing. The deal counts drive the ranking but are not returned, and ties are ordered by workload name in reverse alphabetical order. The list is empty when the company has no qualifying deal. The request body is optional: widget and filters are accepted but do not change the result. Request Examples: Basic request with no filters: { "widget": "top_outsourced_workloads" }
get_account_workforce_trends
ChatGPTGet Workforce Trends Returns a monthly time series of talent flow for the Draup account in the path: total workforce, hires, exits or net gain or loss per month over a time window, or a table with all four measures. It powers the Workforce Trends chart and table on the account's Talent Flow view. Results can be narrowed by location, job family, talent competitor or saved competitor list, and years of experience. The default window is the 12 months ending three months before the current month, with one entry per month labelled by month and year, in chronological order, with zero for inactive months. Total workforce counts stints active at month end, hires count in their start month, exits in their end month, and net gain or loss is hires minus exits. A table request always returns all four measures. Months can be re-sorted by label or value but are not paged. Request Examples: Graph request with locations filter: { "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "req_type": "graph", "response_data": { "locations": { "AND": [ { "OR": [ [ "Sweden", "locations", false, true ] ] } ] } }, "workforce_type": "total_workforce" } Table request with pagination: { "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "req_type": "table", "pagination": { "sortBy": "key", "sortType": "asc" }, "workforce_type": "total_workforce" } Graph request with job families filter: { "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "req_type": "graph", "response_data": { "job_families": { "AND": [ { "OR": [ [ "Account Management", "job_families", false, true ] ] } ] } }, "workforce_type": "total_workforce" } Graph request with time frame filter: { "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "req_type": "graph", "workforce_type": "total_workforce" } Graph request with talent competitors filter: { "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "req_type": "graph", "response_data": { "talent_competitors": { "AND": [ { "OR": [ [ "Nokia Oyj", "talent_competitors", false, true ] ] } ] } }, "workforce_type": "total_workforce" }
get_base_pay_compare_roles_v3
ChatGPTCompare base pay across 2+ job roles (base pay, compare_roles) Annual base salary for 2-10 job roles side by side: pay_data has one row per role and MSA/country passing the talent-size threshold (median_bp, P10/P90, conf_level, reported_salaries). Use for: which role pays more in a place. Not for: titles or experience curve (get_base_pay_ analyze_roles), one role across locations (compare_locations), talent supply (get_talent_size_), benefits (get_top_benefits_), employer pay (get_base_pay_by_companies_), metros in a country (get_base_pay_by_locations_), postings with salaries (get_posted_pay_examples_). Send one MSA or country (several give a row per role x location); regions and states return no rows. Only job_roles and multiple_locations are used. Request Examples: compare_roles: job_roles=Data Scientist,Data Engineer; multiple_locations=United States of America: { "response_data": { "job_roles": { "or": [ "Data Scientist", "Data Engineer" ] }, "multiple_locations": { "or": [ "United States of America" ] } } }
get_core_skill_filter_options_v3
ChatGPTCore skill filter options for a job role, job family or occupation (any scenario) Suggested skills for the given job roles, job families or occupations in data.results[].value, ordered by skill category (root, core, emerging, new, declining) then job-posting frequency; no counts. Soft skills and skills already in core_skills are left out. Use for: choosing skill names to pass as core_skills to other tools. For experience ranges use get_yoe_filter_options_v3; for industry vertical names use get_vertical_filter_options_v3. Not for: a role's categorised skill profile (get_talent_skills_ or get_talent_skills_by_role); skill name look-up (search_core_skills_v3). The analysis scenario does not change the list and is not sent. Send one of job_roles, job_families or job_occupations (first present wins, in that order); several names under one key are pooled. Names must match Draup's spelling exactly, including case (e.g. as returned by search_job_roles_v3); a misspelt name gives an empty list. Skill-only and location-only scenarios have no role, job family or occupation: there only search_key returns suggestions. Locations, verticals and experience have no effect. With none of the three keys and no search_key, data.results is empty. Send pagination.limit 100 (default 10). Before applying a skill, check show_filters from get_talent_size_. Request Examples: One job role: { "pagination": { "limit": 100, "offset": 0 }, "response_data": { "job_roles": { "or": [ "Data Scientist" ] } } } One job family, leaving out a skill already chosen: { "pagination": { "limit": 100, "offset": 0 }, "response_data": { "core_skills": { "or": [ "Python (Programming Language)" ] }, "job_families": { "or": [ "Artificial Intelligence & Data Science" ] } } } One occupation: { "pagination": { "limit": 100, "offset": 0 }, "response_data": { "job_occupations": { "or": [ "Software and Mathematics" ] } } }
get_customers_summary
ChatGPTGet Customers Summary for an Account Returns the customer summary of the account in the path seen as a service provider: how many client accounts actively outsource to it, how many active engagements it holds with them, and its top customers by engagement count. It feeds the Customers section of a vendor's account profile. Engagements are matched to the vendor by its account name, and only engagements flagged active with client accounts visible in Draup are counted. The top customers list pairs each customer name with its engagement count, highest first and then by name, and shows three customers by default, with paging available for that list only. When the account has no customers both counts are zero and the list is empty, and an account not visible to the caller's product returns an empty result. The behavior is identical for Sales and Talent.
get_ecosystem_employers_data
ChatGPTGet Employers Data Fetches employers data based on provided filters such as location, vertical, and sub-verticals. Returns a list of employers with their account details and percentile information. Request Examples: Location - India: { "widget": "employers_v2", "location": "India", "is_country": "true", "analysis_type": "location" } Vertical - Automotive: { "widget": "employers_v2", "vertical": "Automotive", "analysis_type": "vertical" } Location - Capital District, Colombia: { "widget": "employers_v2", "location": "Capital District, Colombia", "analysis_type": "location" } Location with vertical filter: { "widget": "employers_v2", "filters": { "verticals": [ "media & entertainment" ] }, "location": "Greater Los Angeles Area, United States", "analysis_type": "location" } Location with vertical and sub-vertical filters: { "widget": "employers_v2", "filters": { "verticals": [ "media & entertainment" ], "sub_verticals": [ "film & music" ] }, "location": "Greater Los Angeles Area, United States", "analysis_type": "location" }
get_financials_tabs
ChatGPTGet Financials Tabs Returns which Financials sub-tabs have data for the account in the path, as true or false flags, so a client can show or hide the Growth and ratios, Statements, Transcripts, Announcements, Holdings and Conference transcripts tabs of the account Financials page before calling their data APIs. Growth and ratios is on when key-indicator, liquidity or profitability ratio data exists or more than one yearly stock-price point is available for the account's ticker. Statements is on when income statement, balance sheet or cash-flow data exists, Transcripts when at least one quarter-tagged earnings-call transcript exists, Announcements when one was filed in the last 12 months, Holdings when shareholding data exists, and Conference transcripts when conference-call transcripts exist. Only actual, non-forecast financial data counts, and all six flags are always returned for a visible account.
get_globalization_summary
ChatGPTGet Globalization Summary Returns the globalization summary of the company given by id for one business function, or site class: current headcount at its sites, the number of site locations and its globalization index score with the change from the previous record. Use it to size an account's footprint for a given function. A site class is required, chosen from IT, R&D, Sales & Marketing, Customer Support & Service, Legal, Procurement and Finance & Accounting, and an option widens headcount and locations to all of the account's sites. Results can also be limited to sites in one city, state or country. Headcount is summed across the matching sites, and the index score is rounded to two decimals and left empty when there is no index data. With a location limit the index is left out, IT and R&D return headcount while other functions return a headcount range, and the location count is kept only when the location is not a city.
get_job_descriptions
ChatGPTGet Job Descriptions Retrieve job descriptions based on specified filters including job role, location, and skill set. Request Examples: example1: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "skill": { "and": [ { "or": [ [ "project management", "skill", false, true ] ] } ] }, "accounts": { "and": [ { "or": [ [ "1025811508", "accounts", false, true ] ] } ] }, "job_role": { "and": [ { "or": [ [ "project manager", "job_role", false, true ] ] } ] }, "location": { "and": [ { "or": [ [ "greater new york city area, united states", "location", false, true ] ] } ] } } } example2: { "filters": { "job_post_date": { "max": "05-05-2025", "min": "04-06-2025" } }, "query_type": "boolean", "track_total_hits": true, "skipWorkloadReplacement": true }
get_key_account_priorities
ChatGPTRetrieve Key Account Priorities Fetches key account priorities for a given account profile.
get_knowledge_base_data
ChatGPTGet knowledge base data Answers questions about how to use the Draup platform from the Draup help-center knowledge base for the user's product (Sales or Talent): features, pages, workflows, filters, exports, settings, credits, data definitions and methodology. Do not use it for company, talent, job or market data. Returns an answer with links to the help-center articles it used; is_valid is false when the knowledge base has no relevant article. Request Examples: Ask how to use a platform feature: { "query": "How do I add companies to a project?" }
get_location_demographics_data
ChatGPTGet Location Demographics Data Fetches demographic data for a given location. Optionally, specify if the location is a country using the 'is_country' parameter.
get_location_ecosystem_analyze_locations_v3
ChatGPTLocation ecosystem profile of one country or MSA (path scenario analyze_locations) Ecosystem indicators of ONE country or MSA in data.<section>.<attribute>: cost of living, corporate tax, CPI, unemployment, rule of law, political stability and other governance indices, labor freedom, civil liberties, time zone, pollution, crime, travel time to work. Each: value, band (index), change, period, source, definition, up to 5 trend points. The analyze_locations path does not change it. Use for: cost, governance, stability and living conditions of a place. Not for: talent numbers (use get_talent_size_), universities (use get_top_universities_v3), employers (use get_org_top_employers_), pay (use get_base_pay_*). Find attributes by name across sections; one place per call. Request Examples: Profile of a country: { "response_data": { "multiple_locations": { "or": [ "United States of America" ] } } }
get_revenue_by_business
ChatGPTGet Revenue by Business Returns the revenue split by business unit of the Draup account in the path for its latest reported revenue year, with each unit's share of total revenue and its growth over the previous year. It powers the Revenue by Business widget of the Universe account profile and has data only for public companies. Each business unit with non-zero revenue in that year is listed with its revenue in the currency reported by the company, the currency code and the year used. The share is a percentage from 0 to 100 of the sum of all units' revenue that year, and growth is the percent change from the previous year, left empty when the unit had no positive revenue the year before. Units come in no guaranteed order. The result is empty for private companies, for accounts without business-unit data, or when the latest-year total is zero. No filters apply. Request Examples: Basic request with empty filters: null
get_revenue_by_business_v3
ChatGPTGet a public company's revenue split by business unit Returns the revenue of a public company split by business unit for its latest reported revenue year, with each unit's share of the total and its growth over the previous year. Use it to understand a public company's revenue mix and which units are growing. Each unit with non-zero revenue that year is listed with its amount in the reporting currency as reported (typically millions), the currency code and the year used. percentage_share is the unit's percent of the sum of all units that year; shares total 100 including adjustment lines such as Eliminations, which can be negative. growth_percentage is the percent change from the previous year, null when the unit had no positive revenue in the previous year. Units come in no guaranteed order. The result is empty for private companies, for companies without business-unit data, and when business-unit figures for the latest revenue year are not yet available. The endpoint takes no filters. An unknown account ID, or one the caller cannot access, returns an empty response with no result.
get_revenue_by_region
ChatGPTGet Revenue by Region Returns the geographic revenue split of the public company in the path: revenue per reported region for its latest revenue year and the prior year, in millions, with each region's share of the latest year's total revenue. It powers the Revenue by region widget on the account Financials page. Regions appear under their reported names, such as United States or Other Countries, and only when they had non-zero revenue in the latest year; a prior-year entry is added when a prior-year total exists, and its amount can be zero. The latest-year share is the region's amount divided by the account's total reported revenue, as a percentage rounded to two decimals, so shares need not add up to 100. Accounts that are not public or have no regional data return no regions.
get_signal_news
ChatGPTGet news suggestions based on query and filters Fetches news signals using a search query and advanced filter options for categories, verticals, locations, accounts etc. Supports complex boolean logic (AND, OR, NOT) for filtering. Request Examples: Filter by categories with NOT logic: { "query": "mediapost", "response_data": { "categories": { "AND": [ { "NOT": [ [ "Center Setup AND Expansion", "categories", false, true ], [ "Layoff", "categories", false, true ] ] } ] } } } Filter by categories, date_captured and accounts.: { "query": "spirit ceo resigns", "filters": { "date_captured": { "max": "11-12-2025", "min": "10-14-2025" } }, "response_data": { "accounts": { "AND": [ { "OR": [ [ "Google Inc.", "accounts", false, true ] ] } ] }, "categories": { "AND": [ { "OR": [ [ "Executive Movement", "categories", false, true ] ] } ] } } } Query with no filters: { "query": "ai plan of google" }
get_signal_news_v3
ChatGPTGet CoPilot News Suggestions Returns up to 20 recent company news signals captured by Draup that best match a plain-language question, each with its headline, source, link, highlights, dates, categories, locations, companies, your helpful vote and its recent helpful-vote count. It powers the Copilot news search on the Signals page. Only the first search phrase is used as the question. Results can be narrowed by signal category, company vertical, company name or Draup company ID, signal location, saved lists and a capture-date window that defaults to the last 90 days and spans at most 365 days. Candidates must pass a minimum similarity score, are reranked, deduplicated by headline and scored 70 percent on relevance and 30 percent on recency, so the list is not in date order. Highlights are an AI summary when available, otherwise article snippets. API-token callers always get an empty AI summary and no citations, and no match returns empty results. Request Examples: All-of word list; only the first word is used: { "response_data": { "rephrased_query": { "and": [ "Current", "trends", "developments", "in", "the", "global", "regional", "labor", "market,", "including", "hiring", "patterns,", "employment", "statistics,", "workforce", "shifts,", "talent", "acquisition", "dynamics.", "Analysis", "of", "job", "market", "growth,", "unemployment", "rates,", "recruitment", "activity,", "workforce", "participation", "trends." ] } } } Search phrase with an empty capture-date range: { "response_data": { "rephrased_query": { "or": [ "General trends and developments in the labor market, including employment rates, hiring patterns, and workforce dynamics. Analysis of the job market, recruitment environment, and talent landscape." ] } } } Search phrase with a capture-date range: { "filters": { "date_captured": { "max": "08-14-2026", "min": "08-15-2025" } }, "response_data": { "rephrased_query": { "or": [ "Global and regional labor market trends, workforce dynamics, and employment patterns. Developments in hiring, unemployment rates, and shifts in the job market or labor force statistics." ] } } } Search phrase with the summary flag set: { "summary": true, "response_data": { "rephrased_query": { "or": [ "Geographic hubs, innovation centers, and corporate environments where senior mainframe professionals and IBM Z experts show the highest levels of activity and engagement. Regions and organizations with a significant presence of z/OS specialists, COBOL experts, and mainframe modernization talent." ] } } } Any-of search phrase, no filters: { "response_data": { "rephrased_query": { "or": [ "Software engineering salaries and diverse consulting roles offered by Global System Integrators (GSIs) and IT service providers in Chicago. Compensation benchmarks and job titles for software developers and technical consultants within the Chicago professional services and IT services market." ] } } }
get_talent_base_pay_by_companies_roles
ChatGPTGet base pay by company for one job role and location Returns example employers and their median annual base pay for one job role in one metro area or country. Pass the role in filters.job_roles and either a metro area in filters.job_location or a country in filters.job_country; only the first value of each is used, and the call fails with HTTP 400 without a role and a location. The default card view returns a short list of employers spread across the pay distribution, each with account_name, primary_vertical and median_bp (median base pay in local currency), plus currency_code. The plot view returns up to 1,000 employers with reported_salaries (how many salaries each reported) and hml, the 33rd and 67th percentile of that count. With no employer data, pay_data is empty.
get_talent_flow_company_insights
ChatGPTGet Talent Flow Insights for Companies Returns the companies exchanging talent with the Draup account in the path over a time window: where its hires came from, where its leavers went, or the net gain or loss per company, based on Draup's professional profiles. It powers the Talent Flow companies graph and table on the account profile. Hires, exits, net gain or loss, or a combined table can be requested, narrowed by location of the stint at the account, job family, talent competitor or saved competitor list, and years of experience. The default window is the 12 months ending three months before the current month; hires count by stint start and exits by stint end, as stints rather than distinct people. Lists rank largest first, ten by default, and the net view gives that many gainers then losers. The table is paged, sortable and links companies known to Draup; the account's parent and subsidiaries are flagged. Request Examples: Graph request with net_gain_loss and time frame filter: { "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "req_type": "graph", "workforce_type": "net_gain_loss" } Graph request with talent competitors filter: { "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "req_type": "graph", "pagination": { "offset": 0 }, "response_data": { "talent_competitors": { "AND": [ { "OR": [ [ "Nokia Oyj", "talent_competitors", false, true ] ] } ] } }, "workforce_type": "net_gain_loss" } Table request with all workforce types and sorting: { "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "req_type": "table", "pagination": { "offset": 0, "sortBy": "net_gain_loss", "sortType": "asc" }, "workforce_type": "all" } Table request with locations filter and limit: { "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "req_type": "table", "pagination": { "limit": 500, "offset": 0, "sortBy": "net_gain_loss", "sortType": "desc" }, "response_data": { "locations": { "AND": [ { "OR": [ [ "India", "locations", false, true ] ] } ] } }, "workforce_type": "all" } Graph request with locations filter: { "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "req_type": "graph", "pagination": { "offset": 0 }, "response_data": { "locations": { "AND": [ { "OR": [ [ "Sweden", "locations", false, true ] ] } ] } }, "workforce_type": "net_gain_loss" }
get_talent_flow_location_insights
ChatGPTGet Talent Flow Insights by Locations Returns the metro areas where the Draup account in the path gained or lost talent over a time window: hires into and exits from the account per metro area of the stint, or the net gain or loss, with map coordinates. It powers the Talent Flow locations map and table on the account profile. Hires, exits, net gain or loss, or a combined table can be requested, narrowed by location, job family, talent competitor or saved competitor list, and years of experience. The default window is the 12 months ending three months before the current month, with hires counted by stint start and exits by stint end. Only metro areas known to Draup appear, and remote work shows as Remote with placeholder coordinates. Lists rank largest first, ten by default, the net view giving that many gainers then losers; the table is paged and sortable. Sales and Talent behave the same. Request Examples: Table view with all workforce types: { "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "req_type": "table", "pagination": { "offset": 0, "sortBy": "net_gain_loss", "sortType": "asc" }, "workforce_type": "all" } Graph view with net gain/loss: { "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "req_type": "graph", "workforce_type": "net_gain_loss" } Graph view filtered by talent competitors: { "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "req_type": "graph", "pagination": { "offset": 0 }, "response_data": { "talent_competitors": { "AND": [ { "OR": [ [ "Nokia Oyj", "talent_competitors", false, true ] ] } ] } }, "workforce_type": "net_gain_loss" } Graph view filtered by locations: { "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "req_type": "graph", "pagination": { "offset": 0 }, "response_data": { "locations": { "AND": [ { "OR": [ [ "Sweden", "locations", false, true ] ] } ] } }, "workforce_type": "attrition" } Table view filtered by locations: { "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "req_type": "table", "pagination": { "limit": 500, "offset": 0, "sortBy": "net_gain_loss", "sortType": "desc" }, "response_data": { "locations": { "AND": [ { "OR": [ [ "India", "locations", false, true ] ] } ] } }, "workforce_type": "all" }
get_talent_flow_top_metrics
ChatGPTGet Top Talent Flow Metrics Returns one headline talent flow metric for the Draup account in the path over a time window, either workforce growth, hires or exits, as a count plus a percentage from employment stints in Draup's professional profiles. It powers the top metric tiles of the account's Talent Flow view. It honours the same location, job family, talent competitor, saved competitor list and experience filters as other Talent Flow widgets, with a default window of the 12 months ending three months before the current month. Hires count stints started in the window and exits stints ended in it, while growth is the workforce at the window end minus that at the end of the preceding window of equal length. The percentage relates growth to the previous workforce, or hires and exits to the average of current and previous workforce, unrounded. With no previous workforce both numbers are zero. Counts are stints, not distinct people. Request Examples: Hiring metric with monthly time frame filter: { "metric": "hiring", "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } } } Attrition metric with locations filter: { "metric": "attrition", "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "response_data": { "locations": { "AND": [ { "OR": [ [ "Sweden", "locations", false, true ] ] } ] } } } Attrition, 10-39 yrs, Software Developers: { "metric": "attrition", "filters": { "work_experience": { "max": 39, "min": 10 }, "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "response_data": { "job_families": { "AND": [ { "OR": [ [ "Software Developers", "job_families", false, true ] ] } ] } } } Hiring metric with talent competitors filter: { "metric": "hiring", "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "response_data": { "talent_competitors": { "AND": [ { "OR": [ [ "Nokia Oyj", "talent_competitors", false, true ] ] } ] } } } Workforce growth, Software Developers family: { "metric": "workforce_growth", "filters": { "monthly_time_frame": { "max": "05-31-2026", "min": "06-01-2025" } }, "response_data": { "job_families": { "AND": [ { "OR": [ [ "Software Developers", "job_families", false, true ] ] } ] } } }
get_talent_size_breakup_gender
ChatGPTAnalyze talent size breakup by gender for specified roles and filters Returns the gender-wise talent size breakup for the given filters and roles. You can filter by job role, location, skills, and more. The response provides the percentage breakup for male, female, and NA (not available). Request Examples: Analyze Medical Director in Greater New York City Area: { "filters": { "skills": [ "Internal Medicine" ], "job_role": [ "Medical Director" ], "job_location": [ "Greater New York City Area, United States" ], "skill_op_type": "OR" }, "skill_op_type": "OR" } Analyze Human Resources Transformation Manager in United Kingdom: { "filters": { "job_role": [ "Human Resources Transformation Manager" ], "job_location": [ "United Kingdom" ] } }
get_talent_size_breakup_seniority_roles
ChatGPTAnalyze talent pool size breakup by seniority for given filters Analyze the talent pool size breakup by seniority for specified job roles, locations, skills, and verticals. The API supports complex boolean logic for filters. Returns the seniority breakup, median experience, and detailed footnotes. Request Examples: Analyze Internal Medicine Medical Director in Greater New York City Area: { "response_data": { "skill": { "AND": [ { "OR": [ [ "Internal Medicine", "skill", false, true ] ] } ] }, "job_role": { "AND": [ { "OR": [ [ "Medical Director", "job_role", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "Greater New York City Area, United States", "location", false, true ] ] } ] } } } Analyze Human Resources Transformation Manager in United Kingdom: { "response_data": { "job_role": { "AND": [ { "OR": [ [ "Human Resources Transformation Manager", "job_role", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "United Kingdom", "location", false, true ] ] } ] } } } Analyze Content Manager in Greater Los Angeles Area, media & entertainment vertical: { "response_data": { "job_role": { "AND": [ { "OR": [ [ "Content Manager", "job_role", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "Greater Los Angeles Area, United States", "location", false, true ] ] } ] }, "primary_default_verticals": { "AND": [ { "OR": [ [ "media & entertainment", "primary_default_verticals", false, true ] ] } ] } } } Analyze B2B Sales and multiple sales roles in various European regions, retail vertical: { "response_data": { "skill": { "AND": [ { "OR": [ [ "B2B Sales", "skill", false, true ] ] } ] }, "job_role": { "AND": [ { "OR": [ [ "Chief Revenue Officer", "job_role", false, true ], [ "Chief Sales Officer", "job_role", false, true ], [ "Commercial Sales Manager", "job_role", false, true ], [ "Commercial Director", "job_role", false, true ], [ "Head of Sales", "job_role", false, true ], [ "Head of Business Development", "job_role", false, true ], [ "Sales Director", "job_role", false, true ], [ "Vice President - Sales", "job_role", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "Eastern Europe", "location", false, true ], [ "Northern Europe", "location", false, true ], [ "Southern Europe", "location", false, true ], [ "Western Europe", "location", false, true ] ] } ] }, "primary_default_verticals": { "AND": [ { "OR": [ [ "retail", "primary_default_verticals", false, true ] ] } ] } } }
get_talent_size_breakup_seniority_roles_v3
ChatGPTAnalyze talent size breakup by seniority Experience mix of the talent pool under an "analyze_roles" key: breakup_by_seniority maps whole-year buckets of total career experience (0-19, 20 = 20+ years) to % of profiles, plus median_experience. Draup profiles only. Use for: how experienced a role's talent pool is, junior vs senior availability. Not for: talent size in an experience band (use get_talent_size_ with years_of_experience), pay by experience (use get_base_pay_), education (use get_education_background_*). Send 1-25 roles and 1-10 locations (one pooled answer). Years-of-experience filter active: do not call. Read-only; no credits or user context. Request Examples: Filter by job role, core skill, and location: { "response_data": { "job_roles": { "OR": [ "Software Development Engineer" ] }, "core_skills": { "OR": [ "Python (Programming Language)" ] }, "multiple_locations": { "OR": [ "Bengaluru Area, India" ] } } } Filter by job role and single location: { "response_data": { "job_roles": { "OR": [ "Software Development Engineer" ] }, "multiple_locations": { "OR": [ "Bengaluru Area, India" ] } } } Filter by job role, core skill, primary vertical, and location: { "response_data": { "job_roles": { "OR": [ "Software Development Engineer" ] }, "core_skills": { "OR": [ "Python (Programming Language)" ] }, "multiple_locations": { "OR": [ "Bengaluru Area, India" ] }, "primary_default_verticals": { "OR": [ "it services" ] } } } Filter by data scientist role, vertical, and location: { "response_data": { "job_roles": { "OR": [ "Data Scientist" ] }, "multiple_locations": { "OR": [ "San Francisco Bay Area, United States" ] }, "primary_default_verticals": { "OR": [ "consumer software" ] } } } Filter by manager role, multiple core skills, and country: { "response_data": { "job_roles": { "OR": [ "Software Development Manager" ] }, "core_skills": { "AND": [ "Distributed Systems", "Software Development" ] }, "multiple_locations": { "OR": [ "India" ] } } }
get_talent_size_compare_roles_v3
ChatGPTTalent size compared across job roles Talent size per job role (2-10 roles), each pooled across the selected locations: one entry keyed by role name (roles with no data are absent) with size, 95% likely range, 3-year supply growth, RSE, Draup profile count, data_sources and region_countries, plus top-level show_filters. Use for: comparing supply across roles. Not for: one pooled estimate (get_talent_size_analyze_roles_v3), one role across locations (get_talent_size_compare_locations_v3), demand (get_talent_demand_), pay (get_base_pay_). Show: display_talent_size, increase_rate_percentage and display_relative_standard_error, not talent_size, increase_rate or relative_standard_error_pct. Request Examples: Talent size: job_roles=Data Scientist,Data Engineer; multiple_locations=United States of America: { "response_data": { "job_roles": { "or": [ "Data Scientist", "Data Engineer" ] }, "multiple_locations": { "or": [ "United States of America" ] } } }
get_talent_vertical_distribution_roles
ChatGPTCompare talent vertical distribution for job roles Analyze and compare the distribution of talent across industry verticals for specified job roles and locations. Supports advanced filtering and logical operators.
get_talent_vertical_distribution_roles_v3
ChatGPTGet talent vertical distribution for multiple job roles One vertical map per job role (2-10), keyed by lower-case role name as stored in the profile index; roles without matching profiles are absent. With several locations each role's mix covers them combined. Score = profile % x w + posting % (12-month postings) x (1 - w), w = that entry's Draup profiles / its talent size (not capped; 0 when unknown). Use for: comparing the industry mix across roles. Not for: one pooled mix (get_vertical_distribution_analyze_roles_v3), individual companies (get_org_top_employers_), hiring difficulty (get_hiring_difficulty_index_). Show: per-entry share = score / that entry's sum x 100 (1 decimal), not the raw score. Send no vertical or years-of-experience filter. Request Examples: Analyze multiple scientist roles with core skills across US locations: { "response_data": { "job_roles": { "OR": [ "Analytical Scientist", "Applied Scientist", "Fragrance Analyst", "Sensory Scientist" ] }, "core_skills": { "OR": [ "Analytical Techniques", "Experimental Design", "Natural Science", "Performance Analysis", "Performance Testing", "Scientific Problem Solving" ] }, "multiple_locations": { "OR": [ "Greater New York City Area, United States", "United States of America" ] } } } Compare Data Scientist and .NET Developer in Bengaluru Area, India: { "response_data": { "job_roles": { "OR": [ "Data Scientist", ".NET Developer" ] }, "multiple_locations": { "OR": [ "Bengaluru Area, India" ] } } } Analyze leadership product roles with AI core skill in London: { "response_data": { "job_roles": { "OR": [ "Product Director", "Product Management Director", "Head of Technology" ] }, "core_skills": { "AND": [ "Product Strategy", "Artificial Intelligence (AI)" ] }, "multiple_locations": { "OR": [ "Greater London, United Kingdom" ] } } } Analyze manufacturing roles in automotive vertical across specific US MSAs: { "response_data": { "job_roles": { "OR": [ "Manufacturing Technician", "Quality Assurance Technician" ] }, "multiple_locations": { "OR": [ "Cincinnati Metropolitan Area, United States", "Columbus, Ohio Area, United States", "Dayton, Ohio Area, United States", "Greater Grand Rapids, Michigan Area, United States", "Houston, Texas Area, United States", "San Antonio, Texas Area, United States" ] }, "primary_default_verticals": { "OR": [ "automotive" ] } } }
get_tech_stack_trend
ChatGPTGet Tech Stack Trend for an Account Returns the technology products first detected in the tech stack of the Draup account in the path during the last 12 months, each with its category, G2 sub-category, developer company, workloads, countries and usage index. It powers the recently added products view of the account's Tech Stack tab. A product qualifies when its first evidence date at this account falls within the past year, and that date is returned as the date it was added. There is no filtering, paging or sorting: every qualifying product comes back in one response in no guaranteed order. The usage index reads values such as High or Low, and the developer company, workloads and countries can be empty. Dropped products are not listed. The list is empty when no product was first detected in the last year.
get_tech_stack_trend_v3
ChatGPTList technology products a company added in the last 12 months Returns the technology products first detected in one company's tech stack during the past 12 months, with the date each was first detected (added_date), product name and ID, tech stack category, G2 sub-category, developer company, the workloads the product supports, the countries where its use was evidenced and its usage index (High, Medium or Low; rarely NA). Use it to see which tools a company has recently started using. It covers new additions only: it does not report products that were dropped or are in decline, and products first seen more than a year ago are not included (get_account_tech_stack_products_v3 returns the full stack). Every qualifying product comes back in one response, in no particular order (several hundred rows for large companies); there are no filters or paging, and the result is empty when nothing was added in the last year. {id} is the company's Draup account ID, as returned by get_account_id or get_universe_companies_v3. Fields with no value are left out.
get_universe_companies
ChatGPTRetrieve Universe Companies Fetches data about universe companies based on provided filters and pagination options. It will give the accounts with it's account ids.
get_universe_companies_v3
ChatGPTSearch Draup's company directory by filters Returns a page of companies from Draup's company universe as flat rows under response. Each row has logo_url and company_tags plus the columns of the view named in view_name (your saved view of that name, otherwise the product's default columns), keyed by attribute name: identifiers, headquarters, verticals, workforce and hiring metrics, signal flags, tech stack and financial objects with value, year, currency and currencyUnit (USD millions). Entity filters go in response_data as or/and/not lists: competitors expands each chosen company to its top 10 competitors, projects keeps companies saved in those lists, and hiring keys keep companies with matching job postings. Numeric ranges go in filters. search_key adds a company-name contains match and project_id scopes to a project. pagination.sortBy takes a column key (default: your product's opportunity-index score) and sortType the direction; pages hold 10 rows unless limit is set. Each row's account_id is the Draup account id that account tools such as get_account_details_v3 take as id. Request Examples: Opportunity view for companies in a given vertical: { "view_name": "Opportunities", "pagination": { "limit": 25, "offset": 0, "sortBy": "talent_oi_score", "sortType": "DESC nulls last" }, "response_data": { "verticals": { "OR": [ "Enterprise Software" ] } } } Companies by HQ locations in specific US metro areas: { "view_name": "About Company", "pagination": { "limit": 25, "offset": 0, "sortBy": "talent_oi_score", "sortType": "DESC nulls last" }, "response_data": { "hq_locations": { "OR": [ "Greater New York City Area, United States", "San Francisco Bay Area, United States" ] } } } Companies hiring for a specific role in a given location and date range: { "filters": { "hiring_job_postings_interval": { "max": "07-22-2026", "min": "06-23-2026" } }, "view_name": "About Company", "pagination": { "limit": 25, "offset": 0, "sortBy": "talent_oi_score", "sortType": "DESC nulls last" }, "response_data": { "hiring_locations": { "OR": [ "Bengaluru Area, India" ] }, "hiring_job_titles": { "OR": [ "hr analyst" ] } } }
get_vertical_filter_options_v3
ChatGPTIndustry vertical filter options with profile counts (any scenario) Industry verticals in data.results as {key, doc_count}: key = vertical name (lowercase), doc_count = matching Draup profiles, highest first; all verticals in one list, no paging. Verticals already in primary_default_verticals and 'na' are left out; data.percentile is always empty. Use for: which industries can be filtered on and valid names for primary_default_verticals in other tools (pass exactly as returned). For skill names use get_core_skill_filter_options_v3; for experience ranges use get_yoe_filter_options_v3. Not for: the talent split by vertical (get_vertical_distribution_ or get_talent_vertical_distribution_roles_v3); doc_count ranks verticals only and is not talent size. req_type is required: send analyze_skills, compare_skills or compare_locations_skills when the talent pool is defined by skills (core_skills is then applied); any other allowed value ignores core_skills. Send job_roles, job_families and/or core_skills, and/or multiple_locations (location-only is valid for analyze_locations); keys combine with AND. Occupations, filters, pagination and search_key are not applied: for an occupation scenario the list covers all profiles in the location(s); say so when it matters. Before applying a vertical, check show_filters from get_talent_size_. Request Examples: One job role in one metro area: { "req_type": "analyze_roles", "response_data": { "job_roles": { "or": [ "Agentic AI Engineer" ] }, "multiple_locations": { "or": [ "Bengaluru Area, India" ] } } } One core skill in one country, leaving out a vertical already chosen: { "req_type": "analyze_skills", "response_data": { "core_skills": { "or": [ "Python (Programming Language)" ] }, "multiple_locations": { "or": [ "United States of America" ] }, "primary_default_verticals": { "or": [ "enterprise software" ] } } }
get_yoe_filter_options_v3
ChatGPTExperience percentiles and per-year histogram of talent profiles (any scenario) data.percentile.low / high = years of experience at which the cumulative count of matching Draup profiles first reaches 33% / 66%; data.results = per-year {key, doc_count} buckets in ascending order. Bands: Low = 0 to low, Medium = low to high, High = high to 20; cap bounds at 20 and drop a band whose lower bound is 20 or more. Use for: turning 'junior / mid-level / senior' into a filters.years_of_experience range for other tools. For skill names use get_core_skill_filter_options_v3; for industry vertical names use get_vertical_filter_options_v3. Not for: a seniority split of the talent pool (get_seniority_breakup_ or get_talent_size_breakup_seniority_roles_v3). Counts are Draup profiles, not talent size. req_type is required: send analyze_skills, compare_skills or compare_locations_skills when the talent pool is defined by skills (core_skills is then applied); any other allowed value ignores core_skills. Send job_roles, job_families and/or core_skills, and/or multiple_locations (location-only is valid for analyze_locations); keys combine with AND and several names under one key are pooled into one histogram. Occupations, verticals, filters, pagination and search_key are not applied: for an occupation scenario the result covers all profiles in the location(s), and with no applied key it covers all Draup profiles; say so when it matters. Before applying a range, check show_filters from get_talent_size_. Empty results with null low / high: no matching profiles; say the experience bands are unavailable. Request Examples: One job role in one metro area: { "req_type": "analyze_roles", "response_data": { "job_roles": { "or": [ "Agentic AI Engineer" ] }, "multiple_locations": { "or": [ "Bengaluru Area, India" ] } } } One core skill in one country: { "req_type": "analyze_skills", "response_data": { "core_skills": { "or": [ "Python (Programming Language)" ] }, "multiple_locations": { "or": [ "United States of America" ] } } }
role_description
ChatGPTGet Role Description and Metadata Fetches a detailed description and metadata for a specified job role. Optionally, include the 'desc' parameter to request a more detailed description. Request Examples: Request for Medical Director: { "role": "Medical Director" } Request for Human Resources Transformation Manager with desc: { "desc": true, "role": "Human Resources Transformation Manager" }
role_description_v3
ChatGPTGet role description Draup's taxonomy record for ONE job role. Default (desc false): family, occupation, description, responsibilities, core_skills and soft_skills (often null), digitization_quotient with its category, search_assistance_query (Boolean sourcing string), ONET code, title and link, and peer_roles (other roles in its families that have talent data). desc true: only desc (the description) and the ONET fields. Use for: responsibilities, ONET mapping, automation exposure, similar roles in the family, a Boolean search string. Not for: a short definition with family and occupation (get_role_overview_analyze_roles_v3); demand-ranked skills (get_talent_skills_analyze_roles_v3); career moves (get_career_paths_); profiles (get_relevant_profiles_*). Pass one exact, case-sensitive role from search_job_roles_v3 or browse_job_roles_by_family_v3. Request Examples: Sample body payload without desc flag: { "role": "Software Development Engineer" } Sample body payload with desc flag: { "desc": true, "role": "Software Development Engineer" }
search_talent_entities_v3
ChatGPTSearch talent entities (roles, etc.) Type-ahead search over the Talent Intelligence taxonomy that returns job roles, skills, job families and occupations whose names match the search text, ranked by match quality, with a flag showing whether each has talent data in the selected locations. It powers the landing-page search bar. Every word of the search text must appear in the name, ignoring case, and the search can cover one type or all four. The result size, 20 by default, is split evenly across the types searched, so the total is not capped at exactly that number. Matches are ordered by quality, from exact through prefix and word prefix to contains, then by type, roles first and occupations last. With locations selected, names with talent data in every one are marked available and names found only elsewhere are appended as unavailable. When fewer than five results are found, AI-suggested roles or skills are appended. Any internal error returns an empty list. Request Examples: Basic search for 'data scientist' with pagination: { "search": "data scientist", "pagination": { "limit": 50, "offset": 0 } }
suggestions_pay_rate
ChatGPTGet pay rate suggestions Returns suggested pay rate types (e.g., hourly, annually) and their document counts based on provided filters such as salary, currency, job title, skill, location, and more. Request Examples: Basic salary and currency filter: { "filters": { "salary": { "max": 10000000, "min": 1 }, "currency": "USD" }, "options_selected": { "skill_selected": "core_skills" } } Salary, currency, and location filter: { "filters": { "salary": { "max": 200000, "min": 150000 }, "currency": "USD" }, "response_data": { "location": { "AND": [ { "OR": [ [ "greater new york city area, united states", "location", false, true ] ] } ] } }, "options_selected": { "skill_selected": "core_skills" } } Salary, currency, and tech stack filter: { "filters": { "salary": { "max": 100000, "min": 67700 }, "currency": "USD" }, "options_selected": { "skill_selected": "core_skills", "tech_stacks_selected": "tech_stack_products" } } Salary, currency, job title, and location filter: { "filters": { "salary": { "max": 1000000, "min": 500000 }, "currency": "USD" }, "response_data": { "location": { "AND": [ { "OR": [ [ "India", "location", false ] ] } ] }, "job_title": { "AND": [ { "OR": [ [ "product manager", "job_title", false ] ] } ] } }, "options_selected": { "skill_selected": "core_skills", "tech_stacks_selected": "tech_stack_products" } } Salary, currency, job role, location, and job title filter: { "filters": { "salary": { "max": 100000, "min": 80000 }, "currency": "USD" }, "response_data": { "job_role": { "OR": [ { "OR": [ [ "Production Supervisor", "job_role", false, false ] ] } ] }, "location": { "OR": [ { "OR": [ [ "United States of America", "location", false, false ] ] } ] }, "job_title": { "AND": [ { "OR": [ [ "production supervisor", "job_title", false, true ] ] } ] } }, "options_selected": { "skill_selected": "core_skills" } }
talent_demand_top_benefits
ChatGPTGet job benefits data with advanced filters Retrieve job benefits data using complex boolean filters on job attributes such as job title, skill, location, company, and more. Supports pagination and sorting. Request Examples: Filter by job occupation and location: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "location": { "OR": [ { "OR": [ [ "Vietnam", "location", false, false ] ] } ] }, "job_occupation": { "OR": [ { "OR": [ [ "Software AND Mathematics", "job_occupation", false, false ] ] } ] } } } Filter by location, verticals, job roles, and keywords: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "keyword": { "OR": [ { "OR": [ [ "vaccine", "keyword", false, false ], [ "vaccines", "keyword", false, false ], [ "vaccination", "keyword", false, false ], [ "infectious", "keyword", false, false ] ] } ] }, "job_role": { "OR": [ { "OR": [ [ "sales associate", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "sales development representative", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "regional sales representative", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "medical sale representative", "job_role", false, false ], [ "medical sales specialist", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "sales agent", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ] ] } ] }, "location": { "OR": [ { "OR": [ [ "india", "location", false, false ] ] } ] }, "vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "vertical", false, false ], [ "biotechnology", "vertical", false, false ] ] } ] }, "primary_vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "primary_vertical", false, false ], [ "biotechnology", "primary_vertical", false, false ] ] } ] } } } Filter by location, job role, and skill with AND logic: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "skill": { "AND": [ { "AND": [ [ "risk management", "skill", false, true ], [ "project planning", "skill", false, true ] ] } ] }, "job_role": { "AND": [ { "OR": [ [ "project manager", "job_role", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "greater london, united kingdom", "location", false, true ] ] } ] } } } Filter by company: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] } } } Filter by company and location type: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] }, "location_type": { "AND": [ { "OR": [ [ "remote", "location_type", false, true ] ] } ] } } }
talent_demand_top_business_function
ChatGPTVisualize Business Function Demand Returns business function demand data based on provided filters, supporting complex boolean logic and pagination. Request Examples: Pharma/Biotech Sales Roles in India with Vaccine Keywords: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "keyword": { "OR": [ { "OR": [ [ "vaccine", "keyword", false, false ], [ "vaccines", "keyword", false, false ], [ "vaccination", "keyword", false, false ], [ "infectious", "keyword", false, false ] ] } ] }, "job_role": { "OR": [ { "OR": [ [ "sales associate", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "sales development representative", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "regional sales representative", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "medical sale representative", "job_role", false, false ], [ "medical sales specialist", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "sales agent", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ] ] } ] }, "location": { "OR": [ { "OR": [ [ "india", "location", false, false ] ] } ] }, "vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "vertical", false, false ], [ "biotechnology", "vertical", false, false ] ] } ] }, "primary_vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "primary_vertical", false, false ], [ "biotechnology", "primary_vertical", false, false ] ] } ] } } } Project Manager Roles in Greater London with Risk Management Skills: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "skill": { "AND": [ { "AND": [ [ "risk management", "skill", false, true ], [ "project planning", "skill", false, true ] ] } ] }, "job_role": { "AND": [ { "OR": [ [ "project manager", "job_role", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "greater london, united kingdom", "location", false, true ] ] } ] } } } Company and Location Filter: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "singapore", "location", false, true ] ] } ] } } } Company Only Filter: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] } } } Autonomous Vehicle Companies and Keywords with Date Range: { "filters": { "job_post_date": { "max": "04-11-2025", "min": "04-12-2024" } }, "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "OR": [ { "OR": [ [ "may mobility", "company", false, false ], [ "Zipline Inc", "company", false, false ], [ "zoox", "company", false, false ], [ "Motional, Inc.", "company", false, false ], [ "Tesla, Inc.", "company", false, false ], [ "wayve technologies ltd.", "company", false, false ], [ "waymo llc", "company", false, false ], [ "waabi", "company", false, false ], [ "oxa autonomy limited", "company", false, false ], [ "avride", "company", false, false ], [ "aurora innovation, inc.", "company", false, false ], [ "weride", "company", false, false ], [ "pony.ai", "company", false, false ], [ "baidu", "company", false, false ], [ "didi …
talent_demand_top_business_function_v3
ChatGPTTop business functions represented in matching job postings Returns the business functions that matching job postings belong to, meaning departments such as Sales & Marketing, ER&D or Human Resources, ranked by the number of postings in each. It powers the Talent Demand business function chart, showing which parts of a company, vertical or market are hiring for a role, skill or keyword. The posting set can be filtered by title, company or Draup account, location, skill, workload, vertical, function, education and keyword, leaving out staffing firms and job portals if needed, within a posting-date window that defaults to the last 12 months. Up to 500 functions are ranked and paged ten at a time by default, each row giving the function name and its count. The 33rd and 67th percentile counts over all functions are added as low, medium and high colour bands rather than a minimum and maximum. No match returns an empty chart. Allowed keys: benefits, business_functions, certifications, companies, company_tags, core_skills, digital_products, educational_backgrounds, educations, exclusions, job_families, job_occupations, job_roles, job_titles, keywords, languages, location_types, locations, primary_verticals, soft_skills, sub_verticals, verticals, work_types, workloads. Request Examples: Business functions represented in postings from LinkedIn (exact company name): { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "companies": { "or": [ "LinkedIn" ] } } } Business functions for AI-skill postings at jpmorgan chase & co. in the United States: { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "companies": { "or": [ "jpmorgan chase & co." ] }, "locations": { "or": [ "united states of america" ] }, "core_skills": { "or": [ "artificial intelligence (ai)" ] } } } AI-keyword postings in enterprise software within a job-post date range: { "filters": { "job_post_date": { "max": "07-31-2026", "min": "07-01-2025" } }, "pagination": { "limit": 25, "offset": 0 }, "response_data": { "keywords": { "or": [ "Artificial Intelligence", "AI", "Generative AI", "Machine Learning", "LLM" ] }, "primary_verticals": { "or": [ "enterprise software" ] } } }
talent_demand_top_certifications
ChatGPTVisualize certifications with advanced filters Returns certification data based on complex boolean filters for job roles, companies, locations, skills, keywords, and more. Supports pagination and sorting. Request Examples: Pharma/Biotech Sales Roles in India with Vaccine Keywords: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "keyword": { "OR": [ { "OR": [ [ "vaccine", "keyword", false, false ], [ "vaccines", "keyword", false, false ], [ "vaccination", "keyword", false, false ], [ "infectious", "keyword", false, false ] ] } ] }, "job_role": { "OR": [ { "OR": [ [ "sales associate", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "sales development representative", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "regional sales representative", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "medical sale representative", "job_role", false, false ], [ "medical sales specialist", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "sales agent", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ] ] } ] }, "location": { "OR": [ { "OR": [ [ "india", "location", false, false ] ] } ] }, "vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "vertical", false, false ], [ "biotechnology", "vertical", false, false ] ] } ] }, "primary_vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "primary_vertical", false, false ], [ "biotechnology", "primary_vertical", false, false ] ] } ] } } } Project Manager Roles in Greater London with Risk Management Skills: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "skill": { "AND": [ { "AND": [ [ "risk management", "skill", false, true ], [ "project planning", "skill", false, true ] ] } ] }, "job_role": { "AND": [ { "OR": [ [ "project manager", "job_role", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "greater london, united kingdom", "location", false, true ] ] } ] } } } Disney Company Jobs in Singapore: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "singapore", "location", false, true ] ] } ] } } } Disney Company Jobs (All Locations): { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] } } } Autonomous Vehicle Companies and Keywords with Date Range: { "filters": { "job_post_date": { "max": "04-11-2025", "min": "04-12-2024" } }, "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "OR": [ { "OR": [ [ "may mobility", "company", false, false ], [ "Zipline Inc", "company", false, false ], [ "zoox", "company", false, false ], [ "Motional, Inc.", "company", false, false ], [ "Tesla, Inc.", "company", false, false ], [ "wayve technologies ltd.", "company", false, false ], [ "waymo llc", "company", false, false ], [ "waabi", "company", false, false ], [ "oxa autonomy limited", "company", false, false ], [ "avride", "company", false, false ], [ "aurora innovation, inc.", "company", false, false ], [ "weride", "company", false, false ], [ "pony.a…
talent_demand_top_companies
ChatGPTVisualize Account Demand This endpoint allows you to visualize the demand for different companies based on specific skills, soft skills, and verticals, along with defined filters.
talent_demand_top_companies_v3
ChatGPTTop companies hiring for matching job postings Returns the companies with the most job postings matching the filters, ranked by posting count, and marks which of them are companies tracked in Draup's Universe. It powers the Talent Demand top hiring companies chart, showing which employers hire most for a role, skill or location. Company names are taken as written on the postings, so job boards such as Jobs via Dice can appear next to real employers, without the Universe mark. For API-token callers, Universe companies also carry their Draup account id and logo. Filters cover title, company, location, skill, industry, function, education, work arrangement and keyword, with an optional exclusion of staffing firms and job portals, and the posting-date window defaults to the last 12 months. Up to 500 companies are ranked and returned ten per page by default, with 33rd and 67th percentile counts across all companies for colour banding. No match gives an empty list. Allowed keys: benefits, business_functions, certifications, companies, company_tags, core_skills, digital_products, educational_backgrounds, educations, exclusions, job_families, job_occupations, job_roles, job_titles, keywords, languages, location_types, locations, primary_verticals, soft_skills, sub_verticals, verticals, work_types, workloads. Request Examples: Result scoped to a single employer by its exact company name: { "response_data": { "companies": { "or": [ "Walmart Inc." ] } } } Top hiring companies over an explicit 12-month posting window: { "filters": { "job_post_date": { "max": "09-23-2026", "min": "09-23-2025" } } } Top companies hiring for Data Scientist postings: { "pagination": { "limit": 5, "offset": 0 }, "response_data": { "job_titles": { "or": [ "Data Scientist" ] } } }
talent_demand_visualize_core_skills
ChatGPTVisualize core skills distribution Returns aggregated counts of core skills from job postings that match the specified boolean filter criteria. Filters can be applied on fields such as business_function, account_id, and job_title, with support for logical AND and OR combinations. Results can be paginated and sorted by job post date. Request Examples: Business function IT, specific account, Business Analyst titles: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "job_title": { "AND": [ { "OR": [ [ "business analyst", "job_title", false, true ] ] } ] }, "account_id": { "AND": [ { "OR": [ [ 1, "account_id", false, true ] ] } ] }, "business_function": { "AND": [ { "OR": [ [ "it", "business_function", false, true ] ] } ] } } }
talent_demand_visualize_core_skills_v3
ChatGPTGet the top core skills required across job postings matching the given filters Returns the core technical and professional skills most often required in job postings that match the filters, such as Python (Programming Language) or Project Management, ranked by the number of postings asking for each. It powers the Talent Demand skills chart, showing which skills employers hire for at a company, location or job title. A posting counts once for every skill it lists, and names keep Draup catalogue wording with qualifiers. A skill is flagged clickable only when Draup holds adjacent-skill or role data for it, which enables the drill-down in the interface. Filters cover title, company, location, skill, product, industry, function, education, work arrangement and keyword, and the posting-date window defaults to the last 12 months. Up to 500 skills are ranked and paged, ten per page by default, and the 33rd and 67th percentile counts across all skills set the colour bands. No match gives an empty chart. Allowed keys: benefits, business_functions, certifications, companies, company_tags, core_skills, digital_products, educational_backgrounds, educations, exclusions, job_families, job_occupations, job_roles, job_titles, keywords, languages, location_types, locations, primary_verticals, soft_skills, sub_verticals, verticals, work_types, workloads. Request Examples: Company scoped by its exact name: { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "companies": { "or": [ "LinkedIn" ] } } } Core skill plus location filter: { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "locations": { "or": [ "united states of america" ] }, "core_skills": { "or": [ "artificial intelligence (ai)" ] } } } Company plus job-title AND/NOT combination: { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "companies": { "or": [ "Beam Therapeutics" ] }, "job_titles": { "and": [ "medical" ], "not": [ "IT" ] } } }
talent_demand_visualize_digital_products
ChatGPTVisualize digital products talent demand Retrieves talent demand insights based on provided filters and parameters. Request Examples: example1: { "filters": { "job_post_date": { "max": "01-06-2025", "min": "10-09-2024" } }, "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "skill": { "and": [ { "or": [ [ "python (programming language)", "skill", false, true ], [ "structured query language (sql)", "skill", false, true ] ] } ] }, "company": { "and": [ { "or": [ [ "amazon.com", "company", false, true ], [ "apple inc.", "company", false, true ] ] } ] }, "vertical": { "and": [ { "or": [ [ "consumer software", "vertical", false, true ] ] } ] }, "soft_skills": { "and": [ { "or": [ [ "leadership", "soft_skills", false, true ] ] } ] } }, "skipWorkloadReplacement": true }
talent_demand_visualize_education
ChatGPTVisualize education requirements in job postings Returns education distribution for job postings filtered by complex boolean logic on job attributes such as location, company, job role, skill, and more. Request Examples: Filter by job occupation and location: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "location": { "OR": [ { "OR": [ [ "Vietnam", "location", false, false ] ] } ] }, "job_occupation": { "OR": [ { "OR": [ [ "Software AND Mathematics", "job_occupation", false, false ] ] } ] } } } Filter by location, verticals, job roles, and keywords: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "keyword": { "OR": [ { "OR": [ [ "vaccine", "keyword", false, false ], [ "vaccines", "keyword", false, false ], [ "vaccination", "keyword", false, false ], [ "infectious", "keyword", false, false ] ] } ] }, "job_role": { "OR": [ { "OR": [ [ "sales associate", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "sales development representative", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "regional sales representative", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "medical sale representative", "job_role", false, false ], [ "medical sales specialist", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "sales agent", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ] ] } ] }, "location": { "OR": [ { "OR": [ [ "india", "location", false, false ] ] } ] }, "vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "vertical", false, false ], [ "biotechnology", "vertical", false, false ] ] } ] }, "primary_vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "primary_vertical", false, false ], [ "biotechnology", "primary_vertical", false, false ] ] } ] } } } Filter by location, job role, and skills using AND/OR: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "skill": { "AND": [ { "AND": [ [ "risk management", "skill", false, true ], [ "project planning", "skill", false, true ] ] } ] }, "job_role": { "AND": [ { "OR": [ [ "project manager", "job_role", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "greater london, united kingdom", "location", false, true ] ] } ] } } } Filter by company and location using AND/OR: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "singapore", "location", false, true ] ] } ] } } } Filter by company only: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] } } }
talent_demand_visualize_job_title
ChatGPTVisualize job titles Returns aggregated job title data based on boolean filter criteria and pagination options. Request Examples: Filter by business_function, account_id, and job_title with pagination: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "job_title": { "AND": [ { "OR": [ [ "business analyst", "job_title", false, true ] ] } ] }, "account_id": { "AND": [ { "OR": [ [ 1, "account_id", false, true ] ] } ] }, "business_function": { "AND": [ { "OR": [ [ "it", "business_function", false, true ] ] } ] } } }
talent_demand_visualize_job_title_v3
ChatGPTJob posting title distribution for talent demand Returns the job titles found in job postings that match the filters, ranked by posting count, using Draup's normalized lowercase title text such as sales development representative rather than the titles exactly as posted. It powers the Talent Demand job titles chart, showing which roles a company, skill or location segment is hiring for. Because normalized titles are specific, counts form a long tail, with most titles appearing in only a few postings. Postings can be narrowed by title, company or Draup account, location, skill, workload, industry, function, education and keyword, optionally excluding staffing firms and job portals, within a posting-date window that defaults to the last 12 months. Up to 500 titles are ranked and paged, ten per page by default. The response also carries the 33rd and 67th percentile counts over all titles, used as low, medium and high colour bands. No match gives an empty list. Allowed keys: benefits, business_functions, certifications, companies, company_tags, core_skills, digital_products, educational_backgrounds, educations, exclusions, job_families, job_occupations, job_roles, job_titles, keywords, languages, location_types, locations, primary_verticals, soft_skills, sub_verticals, verticals, work_types, workloads. Request Examples: Commercial job titles at a company: { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "companies": { "or": [ "Beam Therapeutics" ] }, "job_titles": { "or": [ "commercial" ] } } } Job titles requiring an AI core skill in the US: { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "locations": { "or": [ "united states of america" ] }, "core_skills": { "or": [ "artificial intelligence (ai)" ] } } } Medical job titles at a company, excluding IT roles: { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "companies": { "or": [ "Beam Therapeutics" ] }, "job_titles": { "and": [ "medical" ], "not": [ "IT" ] } } }
talent_demand_visualize_location
ChatGPTVisualize Talent Demand by Location Returns aggregated job posting counts by location, supporting advanced boolean filtering on job title, skill, location, job post date, and more. The response includes region, country, and geolocation details for each location.
talent_demand_visualize_location_type
ChatGPTVisualize Talent Demand by Location Type Returns aggregated talent demand data by location type, supporting advanced boolean filtering on job postings, companies, roles, and more. Filters can be applied on job title, skill, location, job post date, and other fields. Pagination and sorting are supported. Request Examples: Pharma/Biotech Sales Roles in India with Vaccine Keywords: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "keyword": { "OR": [ { "OR": [ [ "vaccine", "keyword", false, false ], [ "vaccines", "keyword", false, false ], [ "vaccination", "keyword", false, false ], [ "infectious", "keyword", false, false ] ] } ] }, "job_role": { "OR": [ { "OR": [ [ "sales associate", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "sales development representative", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "regional sales representative", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "medical sale representative", "job_role", false, false ], [ "medical sales specialist", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "sales agent", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ] ] } ] }, "location": { "OR": [ { "OR": [ [ "india", "location", false, false ] ] } ] }, "vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "vertical", false, false ], [ "biotechnology", "vertical", false, false ] ] } ] }, "primary_vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "primary_vertical", false, false ], [ "biotechnology", "primary_vertical", false, false ] ] } ] } } } Software Developer/Engineer Roles in Greater Atlanta Area: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "location": { "AND": [ { "OR": [ [ "Greater Atlanta Area, United States", "location", false, true ] ] } ] }, "job_title": { "AND": [ { "OR": [ [ "Software Developer", "job_title", false ], [ "senior software engineer", "job_title", false, true ], [ "software engineer", "job_title", false, true ] ] } ] } } } Jobs at The Walt Disney Company in Singapore: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "singapore", "location", false, true ] ] } ] } } } Jobs at The Walt Disney Company (no location filter): { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] } } } Autonomous Vehicle Companies and Keywords, ER&D Function, Date Range: { "filters": { "job_post_date": { "max": "04-11-2025", "min": "04-12-2024" } }, "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "OR": [ { "OR": [ [ "may mobility", "company", false, false ], [ "Zipline Inc", "company", false, false ], [ "zoox", "company", false, false ], [ "Motional, Inc.", "company", false, false ], [ "Tesla, Inc.", "company", false, false ], [ "wayve technologies ltd.", "company", false, false ], [ "waymo llc", "company", false, false ], [ "waabi", "company", false, false ], [ "oxa autonomy limited", "company", false, false ], [ "avride", "company", false, …
talent_demand_visualize_min_experience
ChatGPTVisualize Minimum Experience Returns the minimum experience distribution for job postings based on complex boolean filters. Supports filtering by job title, skill, location, job post date, and more. Request Examples: Pharmaceutical & Biotechnology Sales Roles in India with Vaccine Keywords: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "keyword": { "OR": [ { "OR": [ [ "vaccine", "keyword", false, false ], [ "vaccines", "keyword", false, false ], [ "vaccination", "keyword", false, false ], [ "infectious", "keyword", false, false ] ] } ] }, "job_role": { "OR": [ { "OR": [ [ "sales associate", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "sales development representative", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "regional sales representative", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "medical sale representative", "job_role", false, false ], [ "medical sales specialist", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "sales agent", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ] ] } ] }, "location": { "OR": [ { "OR": [ [ "india", "location", false, false ] ] } ] }, "vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "vertical", false, false ], [ "biotechnology", "vertical", false, false ] ] } ] }, "primary_vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "primary_vertical", false, false ], [ "biotechnology", "primary_vertical", false, false ] ] } ] } } } Project Manager Roles in Greater London with Risk Management and Project Planning Skills: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "skill": { "AND": [ { "AND": [ [ "risk management", "skill", false, true ], [ "project planning", "skill", false, true ] ] } ] }, "job_role": { "AND": [ { "OR": [ [ "project manager", "job_role", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "greater london, united kingdom", "location", false, true ] ] } ] } } } Jobs at The Walt Disney Company in Singapore: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "singapore", "location", false, true ] ] } ] } } } Jobs at The Walt Disney Company: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] } } } Product Manager and Designer Roles in California: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "location": { "AND": [ { "OR": [ [ "California, United States", "location", false ] ] } ] }, "job_title": { "AND": [ { "OR": [ [ "product manager", "job_title", false ], [ "product designer", "job_title", false, true ] ] } ] } } }
talent_demand_visualize_soft_skills
ChatGPTVisualize Soft Skills Demand Returns a list of soft skills and their demand counts based on the provided filters and boolean query structure.
talent_demand_visualize_soft_skills_v3
ChatGPTSoft-skill demand distribution for talent demand job postings Returns the soft skills most often mentioned in job postings that match the filters, such as Strategic Thinking or Collaboration, ranked by the number of postings naming each. It powers the Talent Demand soft skills chart, showing which behavioural skills a company, role or market segment emphasizes. A posting counts once for every soft skill it lists, and each skill is flagged as clickable only when Draup has drill-down data for it. Postings can be narrowed by title, company, location, core and soft skills, industry, function, education and keyword, optionally excluding staffing firms and job portals, and by posting date, required experience and salary, with the date window defaulting to the last 12 months. Up to 500 soft skills are ranked and paged, ten per page by default, with the 33rd and 67th percentile counts across all soft skills as colour-band thresholds. An empty list means no matching postings. Allowed keys: benefits, business_functions, certifications, companies, company_tags, core_skills, digital_products, educational_backgrounds, educations, exclusions, job_families, job_occupations, job_roles, job_titles, keywords, languages, location_types, locations, primary_verticals, soft_skills, sub_verticals, verticals, work_types, workloads. Request Examples: Commercial job titles at a company: { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "companies": { "or": [ "Beam Therapeutics" ] }, "job_titles": { "or": [ "commercial" ] } } } Postings requiring an AI core skill in the US: { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "locations": { "or": [ "united states of america" ] }, "core_skills": { "or": [ "artificial intelligence (ai)" ] } } } Medical job titles at a company, excluding IT roles: { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "companies": { "or": [ "Beam Therapeutics" ] }, "job_titles": { "and": [ "medical" ], "not": [ "IT" ] } } }
talent_demand_visualize_verticals
ChatGPTVisualize Talent Demand by Verticals Returns talent demand data for specified verticals, supporting advanced boolean filtering on job title, skill, location, company, job role, keyword, and more. Supports pagination and sorting. Request Examples: Pharmaceutical & Biotechnology Sales Roles in India: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "keyword": { "OR": [ { "OR": [ [ "vaccine", "keyword", false, false ], [ "vaccines", "keyword", false, false ], [ "vaccination", "keyword", false, false ], [ "infectious", "keyword", false, false ] ] } ] }, "job_role": { "OR": [ { "OR": [ [ "sales associate", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "sales development representative", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "regional sales representative", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "medical sale representative", "job_role", false, false ], [ "medical sales specialist", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "sales agent", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ] ] } ] }, "location": { "OR": [ { "OR": [ [ "india", "location", false, false ] ] } ] }, "vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "vertical", false, false ], [ "biotechnology", "vertical", false, false ] ] } ] }, "primary_vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "primary_vertical", false, false ], [ "biotechnology", "primary_vertical", false, false ] ] } ] } } } Project Manager Roles in Greater London with Risk Management Skills: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "skill": { "AND": [ { "AND": [ [ "risk management", "skill", false, true ], [ "project planning", "skill", false, true ] ] } ] }, "job_role": { "AND": [ { "OR": [ [ "project manager", "job_role", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "greater london, united kingdom", "location", false, true ] ] } ] } } } The Walt Disney Company Jobs in Singapore: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "singapore", "location", false, true ] ] } ] } } } The Walt Disney Company Jobs (All Locations): { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] } } } Product Manager/Designer Jobs in California, United States: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "location": { "AND": [ { "OR": [ [ "California, United States", "location", false ] ] } ] }, "job_title": { "AND": [ { "OR": [ [ "product manager", "job_title", false ], [ "product designer", "job_title", false, true ] ] } ] } } }
talent_demand_visualize_verticals_v3
ChatGPTTalent demand job-posting counts grouped by industry vertical Returns job postings that match the filters grouped by their primary industry vertical, such as Consumer Software, IT Services or Enterprise Software, ranked by posting count, with an NA bucket for postings that have none. It powers the Talent Demand industry chart, showing which industries drive demand for a skill, keyword set or company. The chart buckets each posting by its default primary vertical, which differs from the vertical filters: one matches any vertical on a posting and another only its primary vertical. Every vertical is returned in one response. Postings can also be narrowed by title, company, location, skill, workload, function, education and keyword, optionally excluding staffing firms and job portals, within a posting-date window that defaults to the last 12 months. The 33rd and 67th percentile counts across verticals are returned for colour banding, and no match gives an empty list. Allowed keys: benefits, business_functions, certifications, companies, company_tags, core_skills, digital_products, educational_backgrounds, educations, exclusions, job_families, job_occupations, job_roles, job_titles, keywords, languages, location_types, locations, primary_verticals, soft_skills, sub_verticals, verticals, work_types, workloads. Request Examples: Company-scoped skill and location filter: { "response_data": { "companies": { "or": [ "jpmorgan chase & co." ] }, "locations": { "or": [ "united states of america" ] }, "core_skills": { "or": [ "artificial intelligence (ai)" ] } } } Core skill filtered to a single location: { "response_data": { "locations": { "or": [ "united states of america" ] }, "core_skills": { "or": [ "artificial intelligence (ai)" ] } } } Broad AI keyword list scoped to a vertical and posting-date range: { "filters": { "job_post_date": { "max": "07-31-2026", "min": "07-01-2025" } }, "response_data": { "keywords": { "or": [ "Artificial Intelligence", "AI", "Generative AI", "GenAI", "Gen AI", "Agentic AI", "AI Agent", "Predictive AI", "AI Engineering", "AI/ML", "Machine Learning", "ML", "Deep Learning", "Natural Language Processing", "NLP", "Computer Vision", "MLOps", "Prompt Engineering", "Large Language Model", "LLM" ] }, "primary_verticals": { "or": [ "enterprise software" ] } } }
talent_demand_visualize_work_type
ChatGPTVisualize work type distribution for job postings Returns the distribution of work types (e.g., Full-Time, Contract, Intern) for job postings based on complex boolean filters on job attributes such as job title, skill, location, company, and more. Request Examples: Filter by job occupation and location: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "location": { "OR": [ { "OR": [ [ "Vietnam", "location", false, false ] ] } ] }, "job_occupation": { "OR": [ { "OR": [ [ "Software AND Mathematics", "job_occupation", false, false ] ] } ] } } } Filter by location, verticals, job roles, and keywords: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "keyword": { "OR": [ { "OR": [ [ "vaccine", "keyword", false, false ], [ "vaccines", "keyword", false, false ], [ "vaccination", "keyword", false, false ], [ "infectious", "keyword", false, false ] ] } ] }, "job_role": { "OR": [ { "OR": [ [ "sales associate", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "sales development representative", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ], [ "sales manager", "job_role", false, false ], [ "regional sales representative", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "medical sale representative", "job_role", false, false ], [ "medical sales specialist", "job_role", false, false ], [ "medical sales manager", "job_role", false, false ], [ "sales agent", "job_role", false, false ], [ "sales specialist", "job_role", false, false ], [ "field sales manager", "job_role", false, false ], [ "field sales representative", "job_role", false, false ], [ "field sales specialist", "job_role", false, false ] ] } ] }, "location": { "OR": [ { "OR": [ [ "india", "location", false, false ] ] } ] }, "vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "vertical", false, false ], [ "biotechnology", "vertical", false, false ] ] } ] }, "primary_vertical": { "OR": [ { "OR": [ [ "pharmaceutical", "primary_vertical", false, false ], [ "biotechnology", "primary_vertical", false, false ] ] } ] } } } Filter by job title and location with AND logic: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "location": { "AND": [ { "OR": [ [ "Greater Atlanta Area, United States", "location", false, true ] ] } ] }, "job_title": { "AND": [ { "OR": [ [ "Software Developer", "job_title", false ], [ "senior software engineer", "job_title", false, true ], [ "software engineer", "job_title", false, true ] ] } ] } } } Filter by company and location with AND logic: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] }, "location": { "AND": [ { "OR": [ [ "singapore", "location", false, true ] ] } ] } } } Filter by company only: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "company": { "AND": [ { "OR": [ [ "the walt disney company", "company", false, true ] ] } ] } } }
talent_demand_visualize_workloads
ChatGPTVisualize Workloads Retrieve workload data based on job title, skill, location, and other filters. Request Examples: example1: { "pagination": { "limit": 25, "offset": 0, "sortBy": "job_post_date", "sortType": "desc" }, "query_type": "boolean", "response_data": { "job_title": { "and": [ { "or": [ [ "Endocrinologist", "job_title", false ] ] } ] } } }
talent_demand_visualize_workloads_v3
ChatGPTTalent demand job-posting counts grouped by workload Returns job postings that match the filters grouped by workload, Draup's functional work category such as Account Management, Artificial Intelligence & Data Science or Application Development & Maintenance, ranked by posting count. It powers the Talent Demand workloads chart, showing which kinds of work drive hiring at a company or for a skill. Postings can be narrowed by title, including titles to leave out, company, location, skill, workload, industry, function, education and keyword, and by posting date, required experience and salary; without a date range the last 12 months up to yesterday are counted. Up to 500 workloads are ranked and paged, ten per page by default, each row giving the workload name and its posting count. The 33rd and 67th percentile counts across the full workload list are returned as low and high colour-band thresholds. No matching postings give an empty list. Allowed keys: benefits, business_functions, certifications, companies, company_tags, core_skills, digital_products, educational_backgrounds, educations, exclusions, job_families, job_occupations, job_roles, job_titles, keywords, languages, location_types, locations, primary_verticals, soft_skills, sub_verticals, verticals, work_types, workloads. Request Examples: Core skill filtered to a single location: { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "locations": { "or": [ "united states of america" ] }, "core_skills": { "or": [ "artificial intelligence (ai)" ] } } } Company scoped with a job-title and/not combination: { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "companies": { "or": [ "Beam Therapeutics" ] }, "job_titles": { "and": [ "medical" ], "not": [ "IT" ] } } } Company scoped with a job-title or/not combination: { "pagination": { "limit": 25, "offset": 0 }, "response_data": { "companies": { "or": [ "Beam Therapeutics" ] }, "job_titles": { "or": [ "commercial" ], "not": [ "IT" ] } } }
talent_filters_suggestions
ChatGPTGet talent pool suggestions Retrieve suggestions for talent pools based on specified filters. Request Examples: Sample request: { "filters": { "job_roles": [ "Administrative Assistant" ] }, "req_type": "analyze_roles", "pagination": { "limit": 100, "offset": 0 }, "filter_type": "verticals" }
talent_filters_suggestions_analyze_roles
ChatGPTGet Talent Filter Suggestions for Analyze Roles Fetches suggestions for talent filters in the Analyze Roles workflow. Allows filtering by job roles, locations, core skills, job families, and more. Supports advanced filter logic and pagination. Request Examples: Analyze roles by job role, location, and core skills (verticals): { "filters": { "job_roles": [ "Medical Director" ], "locations": [ "Greater New York City Area, United States" ], "core_skills": [ "Internal Medicine" ] }, "req_type": "analyze_roles", "pagination": { "limit": 100, "offset": 0 }, "filter_type": "verticals" } Analyze with advanced core skills logic (years_of_experience): { "filters": { "job_roles": [ "Medical Director" ], "locations": [ "Greater New York City Area, United States" ], "core_skills": [ "Clinical Operations" ] }, "filter_type": "years_of_experience", "response_data": { "core_skills": { "AND": [ { "OR": [ [ "Clinical Operations", "core_skills", false, true ] ] } ] } } } Analyze roles by job role and location (core_skills): { "filters": { "job_roles": [ "Human Resources Transformation Manager" ], "locations": [ "United Kingdom" ] }, "req_type": "analyze_roles", "pagination": { "limit": 100, "offset": 0 }, "filter_type": "core_skills" } Analyze with empty response_data (years_of_experience): { "filters": { "job_roles": [ "Human Resources Transformation Manager" ], "locations": [ "United Kingdom" ] }, "filter_type": "years_of_experience" } Analyze roles by job family and location (core_skills): { "filters": { "locations": [ "Bengaluru Area, India" ], "job_families": [ "Software Developers" ] }, "req_type": "analyze_roles", "pagination": { "limit": 100, "offset": 0 }, "filter_type": "core_skills" }
talent_filters_suggestions_compare_locations
ChatGPTGet suggestions for talent filters when comparing locations Returns suggestions for talent filters such as years of experience, core skills, and more, when comparing multiple locations. Supports advanced filter logic, pagination, and search.
talent_filters_suggestions_compare_roles
ChatGPTGet suggestions for talent filters when comparing roles Returns suggestions for talent filters such as core skills, years of experience, and verticals based on the provided job roles, locations, and other filters. Use this endpoint to analyze and compare talent pools for different roles. Request Examples: Compare roles with core skills and location: { "filters": { "job_roles": [ "Food Technologist", "Flavorist", "Seasoning Scientist", "Sensory Scientist", "Food Scientist" ], "locations": [ "Hungary" ], "core_skills": [ "Project Coordination", "Flavor Research", "Equipment Acquisition", "Performance Improvement", "Product Improvement", "General Management", "Process Manufacturing", "Global Regulatory Compliance", "Supply Support", "Sensory Evaluation" ] }, "req_type": "compare_roles", "pagination": { "limit": 100, "offset": 0 }, "filter_type": "core_skills" } Compare roles with years of experience range: { "filters": { "job_roles": [ "Content Producer", "Content Director" ], "locations": [ "Greater Los Angeles Area, United States" ], "years_of_experience": { "max": 20, "min": 10 } }, "req_type": "compare_roles", "pagination": { "limit": 100, "offset": 0 }, "filter_type": "core_skills" } Compare roles with verticals: { "filters": { "job_roles": [ "Content Manager", "Content Director" ], "locations": [ "Greater Los Angeles Area, United States" ], "verticals": [ "media & entertainment" ] }, "req_type": "compare_roles", "pagination": { "limit": 100, "offset": 0 }, "filter_type": "core_skills" } Compare roles for years_of_experience filter: { "filters": { "job_roles": [ "Physician", "Nurse", "Pharmacist", "Therapist", "Physician Assistant", "Dentist", "Clinical Social Worker", "Psychologist" ], "locations": [ "United States of America" ] }, "filter_type": "years_of_experience" } Compare roles with only job roles and locations: { "filters": { "job_roles": [ "Data Science Director", "Data Science Manager", "Data Sciences Consultant", "Vice President - Data Science" ], "locations": [ "Spain" ] }, "req_type": "compare_roles", "pagination": { "limit": 100, "offset": 0 }, "filter_type": "core_skills" }
university_hiring_universities
ChatGPTRetrieve universities with advanced filters and pagination Fetches a list of universities with support for advanced boolean filtering, sorting, and pagination. Filters can be applied on location, job family, field of study, expertise, majors, university, academic location, affiliations, academic title, and search key. Request Examples: Basic pagination request: { "pagination": { "limit": 25, "offset": 0, "sortBy": "academic_research_index", "sortType": "DESC nulls last" } } Filter by location using boolean query: { "pagination": { "limit": 25, "offset": 0, "sortBy": "academic_research_index", "sortType": "DESC nulls last" }, "query_type": "boolean", "response_data": { "location": { "AND": [ { "OR": [ [ "National Capital Region, India", "location", false, true ] ] } ] } } } Empty response_data with boolean query: { "pagination": { "limit": 25, "offset": 0, "sortBy": "academic_research_index", "sortType": "DESC nulls last" }, "query_type": "boolean" } Filter by location and job family: { "pagination": { "limit": 25, "offset": 0, "sortBy": "academic_research_index", "sortType": "DESC nulls last" }, "response_data": { "location": { "OR": [ { "OR": [ [ "Vietnam", "location", false, false ] ] } ] }, "job_family": { "OR": [ { "OR": [ [ "Systems Management & Engineering", "job_family", false, false ], [ "Business Intelligence & Analytics", "job_family", false, false ], [ "Database & Systems Administrators", "job_family", false, false ], [ "IT Security", "job_family", false, false ], [ "Artificial Intelligence & Data Science", "job_family", false, false ], [ "Software & Technology Management", "job_family", false, false ], [ "Software Developers", "job_family", false, false ], [ "Network Administrators & Technicians", "job_family", false, false ], [ "IT Support", "job_family", false, false ], [ "Network Engineering & Architecture", "job_family", false, false ], [ "Software Quality Assurance & Testing", "job_family", false, false ], [ "UI/UX Design & Development", "job_family", false, false ], [ "Telecommunications Engineering", "job_family", false, false ], [ "Web Development", "job_family", false, false ], [ "Actuaries", "job_family", false, false ], [ "Blockchain", "job_family", false, false ], [ "Statisticians", "job_family", false, false ] ] } ] } } } Filter by location and job family with boolean query: { "pagination": { "limit": 25, "offset": 0, "sortBy": "academic_research_index", "sortType": "DESC nulls last" }, "query_type": "boolean", "response_data": { "location": { "OR": [ { "OR": [ [ "Vietnam", "location", false, false ] ] } ] }, "job_family": { "OR": [ { "OR": [ [ "Systems Management & Engineering", "job_family", false, false ], [ "Business Intelligence & Analytics", "job_family", false, false ], [ "Database & Systems Administrators", "job_family", false, false ], [ "IT Security", "job_family", false, false ], [ "Artificial Intelligence & Data Science", "job_family", false, false ], [ "Software & Technology Management", "job_family", false, false ], [ "Software Developers", "job_family", false, false ], [ "Network Administrators & Technicians", "job_family", false, false ], [ "IT Support", "job_family", false, false ], [ "Network Engineering & Architecture", "job_family", false, false ], [ "Software Quality Assurance & Testing", "job_family", false, false ], [ "UI/UX Design & Development", "job_family", false, false ], [ "Telecommunications Engineering", "job_family", false, false ], [ "Web Development", "job_family", false, false ], [ "Actuaries", "job_family", false, false ], [ "Blockchain", "job_family", false, false ], [ "Statisticians", "job_family", false, false ] ] } ] } } }
