AI Search Optimisation Platform

Check your website's AI search readiness.

Enter your domain to assess up to 50 important pages. See what could limit AI discoverability and comprehension, then download and share your report.

Free website readiness check covering up to 50 important pages. Download and share your report.

How it works

The AI Search Flywheel

Traditional SEO is often described through crawling, indexing and ranking. This AI Search Optimisation framework connects three ongoing activities: help AI systems discover your content, make that content easy to understand, and measure where it appears in AI answers. Visibility insights reveal what to improve next, keeping the cycle moving.

STEP 01 · ACCESS

AI Discoverability

Help AI systems find and access the pages that matter. Review crawler permissions, internal navigation, sitemaps and machine-readable discovery signals.

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Each stage informs the next. What you learn from AI visibility helps you refine access, content structure and entity clarity, then measure again.
Start here

Get a broader AI readiness baseline

Review technical readiness before exploring the focused checks below.

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Step 01

AI Discoverability

Make it easier for AI crawlers and agents to access the right parts of your site. Check crawler permissions, llms.txt, machine-readable protocols and content-use preferences before optimizing anything else.

Agentic Resource Discovery Checker

Check ARD manifests, resource descriptions and discoverability signals for AI agents.

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AI Crawlers Compatibility Checker

Check AI crawler access for a specific URL using robots.txt rules, X-Robots-Tag and meta robots signals, with practical fixes.

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Content-Signal Generator

Generate robots.txt Content-Signal directives for search, AI answer input and model training, with publication and verification guidance.

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Emerging Protocols Checker

Check OAuth metadata, API Catalog, A2A, MCP, Agent Skills, ARD, auth.md, WebMCP and emerging agentic commerce protocol signals on a public domain.

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llms.txt Checker

Validate an llms.txt file against proposal v2, review agent-friendly structure and links, and get practical improvements.

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OAuth Discovery Generator

Generate standards-oriented OAuth discovery metadata for authorization servers and protected APIs, with RFC 8414 and RFC 9728 validation.

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Step 02

AI Comprehension

Help AI systems work with content that is clear, well structured and retrievable. Review chunk quality, answer clarity and machine-friendly formats. These checks support comprehension, but do not guarantee citations.

Entity Coverage Analyzer

Analyze named entities, expected-entity coverage, contextual clarity, relationships and schema identity signals.

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Knowledge Graph Explorer

Explore public knowledge graph entities, relationships and identity signals to improve AI search comprehension.

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LLM Chunk Checker

Check page sections for retrieval readiness, standalone context, answer clarity and estimated token size.

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Markdown Negotiation Tester

Test whether a URL serves text/markdown to AI agents through HTTP content negotiation and inspect Content-Type, Vary and response overhead.

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OKF Bundle Generator

Turn up to 50 important website pages into an Open Knowledge Format v0.2 Markdown knowledge bundle with source metadata and ZIP export.

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Step 03

AI Visibility

Visibility is where you evaluate the outcomes of the first two stages. Look at whether your brand, pages and expertise are mentioned or cited in AI-generated answers, which questions you appear for, and which important topics are missing. These observations guide the next round of technical and content improvements.

The feedback loop

Measure, learn, refine

Use citation and mention observations to find unanswered questions, weak entity associations and pages that are not being surfaced. Improve access and content clarity, then check the results again. Strong readiness supports the opportunity to appear in AI search, but does not guarantee citations.