Market Brew models how search engines and large language models evaluate a brand, then shows where a site’s structure, intent coverage and content fall short of what those systems reward. The platform is organised around three jobs: See Structure (query eligibility mapping, signal propagation modelling, centroid stability analysis), Hear Intent (full-site crawl, intent gap detection, embedding validation) and Speak Content (semantic misalignment detection, content gap identification, topical coverage).
What separates it from checklist SEO tools is that it works in embedding space: it measures vector cohesion and semantic alignment between what a site says and the intent it is meant to serve, captures intent signals from first-party data, and predicts the visibility impact of structural changes before they ship. The site adds that each client gets a dedicated LLM deployment. Its trusted-by row shows organisations such as the University of South Florida, Townhall, Salem Media and Texas Scorecard. Forecasting is the claim most worth testing: ask to see a prediction made before a change set beside the result afterwards.
Pricing is not published. Entry is a demo or the Analyze My Brand audit, and a Sign Up button suggests some self-serve access. It is aimed at enterprise brands and SEO teams working on generative-search visibility, a field where measurement standards are still forming, so treat model output as a hypothesis to validate rather than a ranking guarantee.
