Platform Overview

AI Visibility Diagnostics & Monitoring

Five diagnostic checks. Ongoing monitoring. Structured reporting. Built for teams managing AI discoverability at scale.

Five Diagnostic Checks

Each check maps to a tab in the audit report. Run them individually or as part of a full audit.

Crawlability

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.

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Performance

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 →

Content Visibility

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 →

Authority

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 →

Reverse Prompting

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 →

Platform Features

Diagnostic checks run once. Platform features keep the work going over time.

Monitoring

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.

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Reporting

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 →

How Teams Use the Platform

Agencies

Track critical client pages, catch regressions before reporting cycles, and deliver white-label outputs that look like your own work.

In-House Teams

Keep an eye on migrations, releases, and template changes that can quietly damage AI access or render quality.

Consultants

Run audits for discovery, then move problem pages into monitoring when the work becomes ongoing and accountable.

Operators

Use saved history and compare mode to verify fixes, trace regressions, and keep a clean record of what changed.

Full Diagnostic Coverage in One Place

Five checks. Monitoring. Reporting. Everything you need to measure and improve AI visibility, without switching tools.

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