Use the right engine for the right task
- Use language models to interpret questions, summarize evidence and explain results.
- Use quantitative models to calculate ratios, valuations, forecasts, risks and scenarios.
- Use policy and workflow systems to control actions, approvals and reconciliation.
The FinanceGPT architecture
FinanceGPT QLMs coordinate language, LQMs, Knowledge Intelligence, tools and governance. This creates a financial reasoning environment where the user can ask a natural-language question while the actual figure remains traceable to a numerical method or source record.
BUILD WITH FINANCIAL AI
Turn the architecture into an implementation.
Continue into the FinanceGPT developer experience for APIs, SDKs, agents, tools, webhooks, observability and governed financial-AI integration.
Build with FinanceGPT APIs
Research stays public and readable. Product access follows the existing FinanceGPT account and entitlement controls.