AI search & answer visibility (GEO)
Measure whether a brand or domain is cited in AI answers across ChatGPT and AI search engines.
Brand, SEO, and GEO teams measuring how they show up in AI answers.
Public signal is scattered across platforms.
Discovery is shifting from blue links to AI answers, but most SEO tools bolt generative-engine visibility on as an afterthought. An agent needs AI Mode answers with cited sources, LLM-mention tracking, and AI search volume as live records it can pair with classic SERP rank.
AI Mode answers with cited sources
LLM-mention tracking across AI search engines
AI keyword search volume
Visibility gaps and follow-up prompts
Start the agent from a concrete task
Replace the market, brand, competitor, or creator set, then let the agent call UnifAPI MCP only when it needs live public-data evidence.
For these prompts and queries, check whether our brand and domain are cited in AI answers across AI search. Return the cited sources, mentions, AI search volume, and where we are missing.
From public records to a decision brief
Frame the AI-visibility question
Give the agent the prompts, brand terms, and domains you want to track in generative-engine answers.
Fetch GEO records
UnifAPI returns AI Mode answers with citations, LLM mentions, and AI search volume — optionally joined with classic SERP rank from the SEO API.
Report AI vs. organic visibility
The agent shows where you are cited, where competitors win the answer, and which prompts to optimize next, all backed by source records.
APIs this workflow can call
Run it as a Skill, then productize over HTTP.
Use the related Skill when a human wants an agent-ready brief.
Use the API catalog when the workflow graduates into production code.
Keep every public-data call tied to a source URL, request id, and billing record.