Embed AI visibility in your SaaS

Your users are already asking what ChatGPT says about them. If you run an SEO platform, a brand-monitoring tool, a review manager or an agency dashboard, "AI visibility" is a feature your roadmap owes them — and the build-out behind it is six scrapers you don't want to own. This is the use case AgentGEO is shaped for: a data layer that stays invisible under your product. Your backend calls one API; your UI renders your charts from the raw records; your customers never see our name. The alternative vendors in this space are dashboards — they want your users' eyeballs. A data layer wants your API calls.

What you ship: "See what AI says about your brand" as a tab in your product. What you build: one backend integration against a stable JSON contract. What you skip: browser farms, proxy pools, per-engine parsers, and the week each engine's frontend deploy used to cost you.

How the integration works

1. Your backend holds one ag_live_ key. Customers authenticate with you; you call AgentGEO server-side. No per-end-user accounts on our side, no OAuth dance.
2. Fetch on your product's schedule. When a customer adds their brand, your job queue POSTs their query set to /v1/fetches and stores the returned records in your database — answers, citations, sources, provider metadata.
3. Render your feature from your data. Mention rates, citation tables, competitor grids — computed by your code from records you keep. If you later swap vendors or add your own collection, your schema and UI don't move.

// runs nightly per customer brand — Node 18+, no SDK needed
const resp = await fetch("https://api.agentgeo.org/v1/fetches", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.AGENTGEO_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    query: customerQuery,               // from your customer's tracked set
    surfaces: ["chatgpt", "perplexity", "gemini"],
  }),
  signal: AbortSignal.timeout(200_000), // API holds up to 180s on slow surfaces
});
if (!resp.ok) throw new Error(`agentgeo ${resp.status}`);
const run = await resp.json();
await db.aiRecords.insertMany(run.answers.map(a => ({
  customerId, query: customerQuery,
  engine: a.surfaceKey, answer: a.answerText,
  sources: a.sources, fetchedAt: new Date(),
})));

Alternatives

Building on a GEO dashboard's export or reseller program (Profound and peers) means their query model, their refresh cadence and their per-seat economics under your feature. Building the scrapers yourself is the honest comparison — it buys full control and a permanent infrastructure team; the build-vs-buy ledger on that page is written to be argued with.

More use cases

The same integration powers white-label GEO reports for agencies and citation tracking as product features — see all use cases.