AI Discoverability Audit
Can AI systems clearly understand who you are and what you do?
An AI Discoverability Audit assesses how clearly AI systems can identify your organisation, services, products, expertise, locations and proposition. We review website structure, content clarity, company and service entities, structured data, crawlability, service and location information, FAQs, case studies, technical documentation, authority and evidence, machine-readable information and how AI search currently represents you.
The AI Discoverability Audit from Sentry Digital Services shows how clearly AI assistants such as ChatGPT, Claude and Gemini understand and recommend a business, what stops them, and how that changes month by month.
What AI Discoverability Audit delivers
Clearer AI understanding
AI systems get a clearer picture of the company and a more accurate representation of your products and services.
Content gaps identified
We find the gaps and ambiguity that stop an AI system from describing you correctly.
Stronger machine-readable information
Improved foundations for AI search and recommendations.
Measured monthly
An Agent Readiness Report: which AI crawlers read which pages, whether AI assistants recommend you, and who they recommend instead.
Works with your SEO
Complementary improvements to conventional search engine optimisation, not a replacement for it.
Primary tools
Cloudflare
Anthropic Claude
OpenAI
Gemini
PerplexitySecondary tools
Sentry.io
Infisical
Looker
n8n
HermesOne data layer · measured & owned
Every service creates data that is captured, measured and owned.
AI Discoverability Audit doesn’t just run. It generates signal. We land that data in one warehouse and turn it into live KPIs tied to a named owner, so performance is attributable and acted on, never trapped inside a single tool.
Data warehouse
Supabase
Snowflake
Keboola
BigQuery KPIs, dashboards & apps
Plotly
Retool
Apache Superset Platform-agnostic: we connect what you already use and add a warehouse only where it earns its place.
Control over every AI visitor, at no extra cost
Cloudflare's AI Crawl Control shows which AI services read your site and lets you allow or block each one, and Cloudflare verifies which assistants are genuine. Every Astro site we build runs on it.
Cloudflare for your websiteWho it suits
Which websites should consider it
Professional-services, manufacturer and engineering websites, distributors, SaaS and technology businesses, consultants, technical-service companies, and businesses targeting several sectors or geographic markets.
Why it pays: Buyers who shortlist with an AI assistant can drop you before they ever search.
Ecommerce, property, travel, hospitality, healthcare, education and training, financial services, multi-location consumer businesses and local-service providers.
Why it pays: Customers increasingly ask an AI assistant to shortlist before they ever visit a website.
Terms worth knowing
Three terms behind AI discoverability.
The automated reader an AI service sends to fetch your pages, such as GPTBot for ChatGPT or ClaudeBot for Claude.
When you need it: If it cannot read your site, the assistant answers from other people's pages instead.
A plain-text guide at the root of your site that tells AI systems what the business does and which pages matter.
When you need it: It gives an assistant a clean summary instead of leaving it to guess from navigation and design.
Machine-readable labels in the page (schema.org) that state facts such as your services, prices, locations and reviews.
When you need it: Assistants cite facts they can read with confidence; facts buried in design are easy to miss.
Where this sits
Level 1 · Discoverable on the six-level Agent-Ready Web maturity model. See all six levels →
Why this matters
Functional value, value-stream value, and why it can't be ignored.
Reviews how AI crawlers and assistants read your site, checks your llms.txt and structured data for gaps, and reports monthly on crawler reads and whether AI assistants recommend you, or who they recommend instead.
The new front door of the revenue value stream: before a buyer reaches your site, an assistant has often already chosen who to recommend. This service makes sure that choice can include you.
Traditional search engine optimisation asks whether a search engine can find and rank your website. AI discoverability adds another question: can an AI system understand your business well enough to accurately include or recommend it? If the answer is unclear, you may be disadvantaged while customers research with AI assistants.
How we select technology
We choose technology last, for the outcomes it has to earn.
Never tech for its own sake. A tool joins the stack only where it measurably protects value, cuts cost or speeds delivery. It must fit a designed system, be owned where it counts, and be measurable from day one. How we select technology →
Speed
Modern, edge-served stacks are sub-second. Slow surfaces cost conversion and SEO every single day.
Cost
Cut licence, hosting and per-task SaaS fees. Pay for capability, not lock-in or idle enterprise tiers.
Security
Flat, edge architecture with almost nothing left to attack: fewer moving parts, smaller surface.
Ownership & no lock-in
Composable and self-hosted where it counts, so you own the system, not rent someone else’s.
Measurability
Clean data and KPIs built in. You cannot improve, automate or apply AI to what you cannot measure.
Fit to process
The right tool for a designed system, selected against process readiness, so it amplifies, not adds friction.
How we deliver · DMAIC
Every AI Discoverability Audit engagement runs on DMAIC.
Define the goal and its value, measure the baseline, analyse the real constraint, improve with a proven build, then control the gains, so results are predictable, repeatable and defensible, not down to luck.
Agree the goal, value, budget & timescale up front.
Baseline the KPIs above: current state, not guesswork.
Diagnose the real constraint and the solution needed.
Build the chosen solution; prove the uplift.
Lock in the gains; monitor and sustain them.
FAQ
Common questions
What does the AI Discoverability Audit cost?
Sentry starts with a baseline Agent Readiness Report at a promotional price of £500, refunded in full if you go ahead with the project. The fixes are then priced as a fixed project, a monthly support plan, or as part of a managed Growth Engine engagement, quoted after the baseline.
Will this improve my Google ranking?
Sentry does not promise that. The aim of the AI Discoverability Audit is to be found, recommended and used by AI assistants, which is a separate channel from Google rankings.
What is WebMCP and do I need it?
WebMCP is a proposed web standard that lets a website tell AI agents which actions it offers, such as requesting a quote. It is developed in the W3C Web Machine Learning Community Group and in trial in Chrome and Edge. Sentry adds it through WebMCP Form Enablement on forms you already have, with nothing changing for human visitors.
Do I need a new website?
No. Most AI discoverability fixes work on an existing website. Sites that Sentry rebuilds in Astro on Cloudflare get them as standard.
How is AI discoverability measured?
Sentry's monthly Agent Readiness Report shows which AI crawlers read which pages, whether AI assistants recommend the business for its buyers' questions, which competitors they recommend instead, and whether AI browsing agents can complete the site's key journeys.
Why does Sentry build on Cloudflare for this?
Cloudflare's AI Crawl Control, available on all plans, shows which AI services read a site and lets the owner allow or block each one, and Cloudflare verifies which bots and AI agents are genuine. Sentry runs its own AI-visitor log on Cloudflare: in 63 hours from 22 to 25 September 2026 it recorded 769 page reads by 16 AI crawlers on sentrydigitalservices.com, 472 of them verified by Cloudflare.
Start here · the free first step
AI Discoverability Audit starts the same way every engagement does: with Discovery.
Two distinct moves: a free, no-obligation Discovery Session to find your value at stake, then the Discovery & Blueprint: 14 structured outputs (value model, roadmap and business case) before a pound of delivery is committed.
Engaged alone or as one engine