Readers no longer just search Amazon and Google — they ask ChatGPT, Claude, Perplexity and Gemini what to read next. The AI Discovery Audit tests your book against all four, then hands you the exact fixes to get recommended: a ready-to-paste listing rewrite, schema snippets, and a confidence-tagged action plan.
In 2026, the question isn't just "does my book rank on Amazon?" — it's "when a reader asks an AI what to read, does my book come up?"
ChatGPT alone fields billions of searches a week. Perplexity ships as the default engine in new browsers. Claude and Gemini answer reading questions all day. These models are becoming the first place readers go for a recommendation — and if they don't know your book, no amount of Amazon Ads spend plugs that hole. This is AEO — answer-engine optimisation, the new layer on top of SEO, and almost no indie author is doing it yet.
Plenty of tools now track how AI sees big brands. This is the world's first AI-discovery audit built for books — the only one that tests how AI recommends your title, maps the sources behind the books that beat it, checks whether you were scraped into the training data, and rewrites your Amazon listing for Rufus. If AI is the new way readers search, this is how you make sure they find you.
Most AI-visibility tools track brands. This one is built for how AI recommends books — and it doesn't just score you, it hands you the fixes.
We run your book across ChatGPT, Claude, Perplexity & Gemini, multi-pass — using the questions readers actually ask, mined live from Reddit, Amazon "customers also searched", and Google "people also ask". Not made-up prompts.
The books AI recommends instead of yours, plus the precise sources and links it cites for them — so you know exactly where to get mentioned to break in.
We check whether your title sits in the datasets and shadow libraries (Anna's Archive, Books3) used to train today's models — and if it does, you get pre-filled copyright-assertion letters.
Ready-to-paste title, subtitle, description and your 7 backend keyword slots — rewritten for how Amazon's Rufus AI actually reads a listing, not keyword stuffing.
The exact paste-ready schema/structured-data snippets and a Wikidata plan that make machines recognise your book — and you as an author entity.
Whether AI crawlers can actually reach and read your book pages and website. If they're blocked, nothing else matters — so we check first.
Where you can realistically win recommendations, and which comparable titles to position against — instead of fighting battles you can't win.
Every fix labelled by likely impact — direct cause-and-effect vs. worth-a-try — so you start with what actually moves the needle.
£29.99
One price, the full audit — the four-engine test, the rewrite, the schema kit, the scrape scan and the roadmap. No upsell tiers, no holdbacks.
Get the full audit →Risk-free to try first — preview a real sample report or run the free 90-second score. One payment, no subscription.
| Free AI Discovery Score | Full AI Discovery Audit | |
|---|---|---|
| Tells you if AI can find your book | ✓ | ✓ |
| Four-engine test on real reader queries | ✓ | ✓ |
| Who's recommended instead — and their sources/links | — | ✓ |
| Amazon listing rewrite + 7 backend keywords | — | ✓ |
| Schema, Goodreads & Wikidata snippets | — | ✓ |
| "Was your book scraped?" scan + defense letters | — | ✓ |
| Competing-titles battle zone | — | ✓ |
| Confidence-tagged action roadmap | — | ✓ |
| Price | Free | £29.99 |
Yes. Readers increasingly ask ChatGPT, Claude, Perplexity and Gemini for recommendations — "what's a good book on X?", "books like Y". The models answer from training data and live web search. If your book and author aren't recognised, you're invisible at the point of recommendation.
A multi-pass retrieval test across the four major AI engines, plus a ready-to-paste Amazon listing rewrite, schema and Wikidata snippets, a check of whether your book appears in the major AI training datasets, and a confidence-tagged action roadmap. £29.99.
The full audit is £29.99 — one price, no upsell tiers. There's also a free 90-second AI Discovery Score that tells you whether the models can find your book before you buy.
Yes. Traditional SEO optimises for Google's ranked links. AI discovery — sometimes called AEO (answer-engine optimisation) or GEO (generative-engine optimisation) — optimises for whether a model retrieves and recommends you in a written answer. Structured data, author entity recognition and citation sources matter more. See our guide to AI book discovery.
Most AI-visibility trackers are built for brands and SEO teams. This is built for books: it tests the real recommendation questions readers ask, maps the exact sources behind the books that get recommended, checks whether your book was scraped into AI training data, and rewrites your Amazon listing for Rufus — all in one report.
Self-published and indie authors, and small presses, who want their books found by readers using AI search. It works for any title with an Amazon listing — fiction or non-fiction.
The free diagnostics and the guides behind the audit.
Why answer-engine optimisation matters for authors in 2026 — and the signals that decide whether AI recommends you.
Read the guide →The practical steps to become visible to ChatGPT, Claude, Perplexity and Gemini.
Read the guide →KDP Readiness, Cover Readiness, Advertising Readiness and the free AI Discovery Score.
Run a free audit →