White-label AI visibility data for agencies and platforms
If you run an agency or an SEO platform, your clients are already asking “do we show up in ChatGPT?” You can answer that inside your own product this quarter — without standing up a browser fleet.
The white-label shape
Your backend calls one API; your frontend shows your brand. The API is the invisible layer:
- Client dashboards: per-client prompt sets, mention rate and citation share trends, market splits — all computed from stored responses.
- Automated reports: a weekly job pulls each client’s prompts, diffs mention/citation numbers, renders the PDF or email.
- Prospecting tool: run a prospect’s category prompts before the pitch; walk in with “here’s where you’re invisible.”
- Product surface: platforms can resell it as a module — an “AI visibility” tab powered by your own plan margins.
What the data gives you
Every response carries what a client-facing report needs: the full text/markdown answer to quote verbatim, sources[] to show who else is cited, entities[] for brand detection, searchQueries[] to explain why the answer said what it did, and commerce cards for product clients. Geo parameters mean a multinational client gets per-market views from one integration.
Economics that work
Usage-based credits mean your cost scales with client volume, not headcount. A mid-tier plan covers thousands of monitored prompts monthly; per-client marginal cost is a few dollars against whatever you charge for the module. Plans go up to enterprise volumes, and expansion is the point — add engines, markets and prompts as clients buy in.
Getting there
Start with the quickstart, wire one client’s prompt set through an async batch with webhooks, and you’ve validated the whole pipeline before writing a line of dashboard UI. The TypeScript and Python SDKs are thin typed wrappers — nothing exotic to maintain.