Render the real page
PageLens AI loads the public URL in a browser, captures screenshots and reads the rendered DOM, headers, links, structured data and page metrics.
Launch readiness methodology
The inspection framework behind every PageLens AI report.
PageLens AI combines browser evidence, deterministic rules and AI-assisted judgement to decide whether a public website is ready for real visitors, buyers, search engines and AI answer engines.
How a PageLens AI inspection works.
The methodology separates hard evidence from judgement. That keeps reports repeatable while still surfacing the launch problems that require context.
Run deterministic checks
Rules inspect evidence that should not depend on model judgement: accessibility output, status codes, headers, metadata, tracking, crawl signals and known technical patterns.
Apply AI-assisted review
AI review is used where judgement helps: clarity, trust, buyer path, AI answerability, content fit, mobile usability and site-context relevance.
Score and prioritise
Findings are severity-rated and category-tagged, then rolled into a versioned score and action plan that stays comparable across rescans.
Evidence captured
What the report can point to.
- Rendered screenshots and viewport context
- HTML, headings, links, metadata and structured data
- HTTP status, redirects, canonical and sitemap signals
- Security headers, cookies and visible third-party scripts
- Accessibility output and contrast evidence
- Core Web Vitals style lab and field signals where available
- Accepted-risk and intentional-trade-off decisions
Boundaries
What PageLens AI deliberately does not claim.
- PageLens AI is not a penetration test or vulnerability assessment.
- PageLens AI is not legal, compliance or accessibility certification advice.
- A scan is not a full replacement for human QA on complex product workflows.
- AI-assisted findings are evidence-led, but owners can accept, defer or dispute findings that reflect deliberate trade-offs.
A system built to improve over time.
Every scan stores the scoring version used at the time. As PageLens AI evolves, historical reports remain explainable and new benchmark data can show how launch readiness changes across the web.