Fay

Fay is an AI-powered research service that runs asynchronous research tasks and reports back via webhooks. From the documentation, it’s aimed at developers and product teams who want to kick off research jobs (for example, market or competitive research) and get notified programmatically when results are ready, when status changes, or when something fails.

You manage webhook configuration through the Fay web dashboard, where you register an HTTPS endpoint, choose which event types you want (Status, Output, Error), and obtain a secret for signature verification. Your application exposes a standard HTTP endpoint to receive JSON payloads, then routes each event type into your own workflows.

Fay’s webhook system is designed for robust backend integrations: events are structured, include request and conversation identifiers, and are signed using HMAC-SHA256 via an X-Fay-Signature header. The docs provide concrete examples in Node.js/Express and Python/Flask for validating signatures and handling events, which makes implementation straightforward for most web backends.

However, the available documentation here focuses narrowly on webhooks and doesn’t describe the underlying AI models, data sources, or privacy guarantees behind the research itself. Pricing and rate limits are also not documented on this page. Non-technical users looking for a simple, consumer-facing research assistant may find Fay too developer-centric, since you need to set up and maintain an HTTPS endpoint and server-side logic. If you require detailed compliance information or no-code integrations, you’ll need to look beyond this webhook documentation or contact the vendor directly.