Finance

AIR Credit Intelligence

by AIR Platforms, Inc.

Overview

AIR Credit combines powerful machine learning credit intelligence with AI agents directly inside ChatGPT. Instantly assess companies, uncover emerging credit risks before they become obvious, understand the drivers behind every rating, and test future scenarios in seconds. Whether you're evaluating counterparties, investments, suppliers, or borrowers, AIR helps you make faster, more informed decisions without leaving the conversation.

Tools

get_credit_rating

ChatGPT

Get the latest AIR Credit Risk Score and AIR Rating for a resolved company. Returned fields: - air_credit_risk_score: AIR's proprietary credit risk score (numeric, 0-1). Refer to this as "AIR Credit Risk Score" when presenting results to the user. - air_rating: closest matching AIR Rating letter grade (e.g. "BBB"). Refer to this as "AIR Rating". Pass company_id (a UUID returned by get_entity).

get_entity

ChatGPT

Search AIR companies by fuzzy name or ticker and return possible entity matches. The response contains a status field: exact_match (one literal name/ticker hit), multiple_matches (the caller MUST ask the user to disambiguate), or no_match. Never auto-select a company from multiple_matches — always confirm with the user first.

get_rating_explanation

ChatGPT

Explain the latest AIR credit rating using AIR model drivers and financial context. Pass company_id (a UUID returned by get_entity).

run_credit_scenario

ChatGPT

Run a stateless AIR credit scenario and return predictions plus financial parameters. Results are NOT stored. IMPORTANT: this tool does NOT accept a natural-language question. The CALLER must translate the user's scenario into a changes array before calling. Each item in changes has: - field: one of revenues, cost_of_revenue, operating_expenses, interest_expense, research_and_development, long_term_debt, liabilities, inventory, accounts_payable, net_cash_flow_from_operating_activities, net_cash_flow_from_investing_activities, net_cash_flow_from_financing_activities - change_type: 'percent' or 'absolute' - change_value: number. For percent use a fraction (-0.20 = -20%, 0.05 = +5%). For absolute use the raw dollar amount (e.g. -1000000000 = -$1B). - year: integer >= 1 (default 1 = first projected year) Translation examples: 'revenues fall 20% next year' -> [{field:'revenues', change_type:'percent', change_value:-0.20, year:1}] 'operating expenses up 5%' -> [{field:'operating_expenses', change_type:'percent', change_value:0.05, year:1}] 'long term debt down $1B' -> [{field:'long_term_debt', change_type:'absolute', change_value:-1000000000, year:1}] 'revenues -10% AND opex +5% in year 2' -> [{field:'revenues', change_type:'percent', change_value:-0.10, year:2}, {field:'operating_expenses', change_type:'percent', change_value:0.05, year:2}] If the user's scenario cannot be expressed using these fields, ASK the user to rephrase using one of the supported fields instead of skipping the call. Always pass company_id (UUID from get_entity) plus a non-empty changes array.

Links

Documentation ↗Privacy Policy ↗

App Stats

Tools

ChatGPT

Platforms