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Buying question

How should a team compare AI observability pricing across traces, events, retention, evaluator runs, seats, and data volume?

Which brands each model API named when asked this question, and which pages it cited. Answer text is not published.
Snapshot Oct 22, 2026. Each category is re-run in rotation, every few weeks.

Commercial

Kind of question

3

Model APIs

0

Brands named

0

Pages cited

Brands

Brands the answers named

Rank#BrandModel APIsMentionsNamed by

Model APIs

What each model API returned

Model APIModelBrands namedCitationsDomainsAnswer hash
OpenAIopenai/gpt-6-lunaNone named00198efece…34a82
Anthropicanthropic/claude-haiku-5.5None named00889a5d1d…a1bd9
Googlegoogle/gemini-3.1-flash-liteNone named0068265d17…65bc9
Snapshots
b508948a-6a42-4345-b118-2d4a4bb38b87
Question set
llm-observability-platforms-2026-07-27
Benchmark version
4-llm-observability-platforms-2026-07-27-models-16124f05e021
What is kept
Measured in AI observability. Full answers are not stored or published, and no customer data is included.

Enter your website. In about two minutes, Rank.ai asks ChatGPT, Claude and Gemini 12 questions your customers ask and grades how often they name you.

  • Your grade out of 100How often AI names you, cites your site, and how high it ranks you.
  • Who gets namedEvery competitor in the answers, most named first.
  • The pages AI readsThe sources behind each answer.
  • Three fixesWhat to fix first, with a brief for the first article.