# Benchmark how AI represents you

> KnitKnot runs a stable library of buyer questions across supported AI engines, then preserves the answers, claims, competitive outcomes, and source evidence behind the result.

- Canonical: https://knitknot.ai/product/benchmarking/
- Part of: Get Agent Ready

## Start with a frozen baseline

The first benchmark records how AI represents your company before managed content is published. Questions are organized around the journeys and categories the customer chooses. Organic visibility, head-to-head outcomes, and misrepresentation are kept separate because they answer different questions.

## Read the evidence behind the result

Each result links back to a captured answer. Material claims retain their verdicts and receipts. Source attribution appears only when the response exposes a reliable signal; it is not guessed.

## Keep the comparison stable

KnitKnot preserves the active question library, engine, model-version context, and included answer cells. Later cycles use the same measurement grain so movement is interpretable.

## The benchmark has a second job

The evidence becomes the input to managed agent content. Vocabulary gaps, repeated misrepresentations, category coverage, and approved company facts are assembled into a typed evidence packet for eligible pages.

## Boundary

A KnitKnot benchmark is a repeatable measurement of supported execution paths. Personalization, location, account history, and model updates can produce a different answer for an individual buyer.