Five diagnostic checks. Ongoing monitoring. Structured reporting. Built for teams managing AI discoverability at scale.
Each check maps to a tab in the audit report. Run them individually or as part of a full audit.
Robots.txt rules for 33 AI bots, live HTTP status per bot, noindex detection, and redirect chain analysis. Near-certain signal — a bot is either blocked or it isn't.
Learn more about crawlability →TTFB, CLS, and INP from Chrome UX Report field data. Graded A+ to F with AI-specific thresholds — a slow TTFB fails the AI crawl gate regardless of Content Web Vitals score.
Learn more about performance →Compares JS-rendered HTML against raw bot HTML for GPTBot, ClaudeBot, and PerplexityBot. Surfaces content that exists for users but disappears for crawlers.
Learn more about content visibility →Schema.org validation, JSON-LD completeness, page-type classification, and metadata signals. Measures what AI systems use to evaluate source credibility.
Learn more about authority →LLM-based analysis of which prompts your content is positioned to answer — predicts page fit, not live AI rankings. Medium confidence, high actionability.
Learn more about reverse prompting →Diagnostic checks run once. Platform features keep the work going over time.
Schedule recurring audits on tracked pages. Get alerted when scores drop, compare results across runs, and ingest pages in bulk via batch import. Designed for teams managing visibility at scale.
Learn more about monitoring →Export full audit reports as PDFs, generate shareable links for clients and stakeholders, and white-label outputs with your own branding. Reports save automatically and stay in your history.
Learn more about reporting →Track critical client pages, catch regressions before reporting cycles, and deliver white-label outputs that look like your own work.
Keep an eye on migrations, releases, and template changes that can quietly damage AI access or render quality.
Run audits for discovery, then move problem pages into monitoring when the work becomes ongoing and accountable.
Use saved history and compare mode to verify fixes, trace regressions, and keep a clean record of what changed.
Five checks. Monitoring. Reporting. Everything you need to measure and improve AI visibility, without switching tools.
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