seo-geo

To optimize content for AI Overviews and ChatGPT search, you need to evaluate citability, structure, and media readiness. This GEO analysis assesses brand signals, readability, and multi-modal assets to generate a structured report with prioritized remediation steps for AI-driven discovery.

An llms.txt file signals AI crawler readiness and boosts discoverability across major AI search platforms. GEO analysis checks your llms.txt presence alongside robots.txt to determine crawler access status and provides guidance on improving AI search platform indexing.

Checking if a blog post is citable by Perplexity involves evaluating passage-level citability blocks, structural readability, and authority signals. A GEO readiness assessment scores these criteria and provides a platform breakdown to maximize AI citations.

GEO optimization works for technical documents, product pages, and marketing content where AI overviews and citability matter. The analysis applies authoritativeness checks, multi-modal asset reviews, and SSR checks to ensure AI-driven discovery across various content types.

The best way to improve structural readability for AI search engines is to assess content formatting through a GEO readiness report. This evaluation scores structural readability, identifies missing passage-level citability blocks, and outputs prioritized remediation steps.

Content not showing in Google AI Overviews despite good SEO often lacks specific GEO signals like passage-level citability blocks, llms.txt status, or proper multi-modal assets. A GEO analysis identifies these gaps with platform-specific breakdowns and remediation workflows.