Free AEO & SEO Auditor — Check if AI Search Knows Your Business
Does AI know your business exists? Type any URL and we'll score it against the awesome-aeo-seo research framework — how AI search (ChatGPT, Google AI Overviews, Gemini, Perplexity) actually retrieves and cites — and hand you a prioritized fix list.
Scanning page, llms.txt, robots.txt & sitemap…
Server-side fetch — works on any public site. Powered by Kavenacc VentureForge AI.
🏛 Kavenacc Digital Solutions26 yrs IT & software50+ apps shippedAuthor: “The Future of Work in the New AI Era”Framework: awesome-aeo-seo
0
—
Dimension scores
Weighted by the awesome-aeo-seo evidence hierarchy: prompt-content alignment > earned media > structure. Schema / Core Web Vitals carry no independent citation signal, so they are weighted low by design.
Dimension
Score
Bar
Evidence
Prioritized loopholes
Fix top-down. HIGH gaps move the needle most for AI visibility.
Severity
Dimension
Score
Evidence / why it matters
Running the full pre-launch audit…
Probing the site as six different crawlers — a browser, Googlebot, GPTBot, OAI-SearchBot, ClaudeBot and PerplexityBot — then checking parity, retrievability, schema, agent usability and security. 30–60 seconds.
Fetching the page as an AI crawler…
The deep audit could not finish.
AI Readiness Index
A second, deeper score. The AEO score above rates how well this page is written for AI answers. This one asks whether machines can reach, read and act on the site at all — across six weighted pillars. It measures retrievability, not authority: it cannot tell you whether an engine will cite you.
0
—
The one thing
Pillar scorecard
Weights are the published AI Readiness Index weights. Coverage is how much of each pillar this server-side engine could actually measure — anything needing a real browser is excluded from the score rather than guessed at.
Pillar
Score
Weight
Bar
Coverage
Launch blockers & fixes
P0 blocks a launch. P1 is fix-within-24-hours. Each carries what was measured, why it costs you money, where to fix it, and the exact command to prove it is fixed.
Live crawler probe
The page fetched once per user-agent. This is the check robots.txt cannot answer: whether a CDN or prerender rule quietly serves AI crawlers something different from Googlebot.
User-agent
Status
Words received
Challenged
Launch-day checklist
Expected pre-launch blocks. Normal to have — they must come off at go-live.
What is already good
What this audit did not test
Listed so you know exactly where the coverage ends. Nothing here was estimated or scored — an untested check is removed from the calculation, never counted as a pass or a fail.
Want this fixed for you? Kavenacc builds AEO-ready sites, llms.txt files, AI-crawler robots.txt and FAQ schema as standard. Tap the WhatsApp button → ask for an AEO build.
Privacy: your score, dimension breakdown and loophole list are generated from public page data only and are always free. When you ask us to email your PDF report, we store the email you provide (and link it to your domain + score) solely to send that report and a few free AEO tips — you can unsubscribe anytime. We never sell audit data. Aggregate audit counts (domain + score) are logged to measure demand.
The problem
Traditional SEO got your site to rank. But now customers ask ChatGPT, Gemini and Perplexity — and those engines cite pages by alignment, authority and earned mentions, not your keyword density. Most sites are invisible to the answer engine and have no idea why.
Why this matters
The auditor is built on published AEO research — not guesswork.
Answer engines now decide a growing share of discovery. The evidence is clear about what actually drives a citation:
1
Prompt-content alignment dominates
A 2M-point citation study found alignment of content to how a model frames a query is the single largest signal — ~3× the next.
2
Earned media beats owned
Third-party authoritative mentions outperform your own pages inside AI answers. Schema shows no independent citation signal.
3
llms.txt is the new robots.txt
A machine-readable context file tells LLMs who you are and corrects stale directory listings — directly fighting misinformation.
4
SEO is still the floor
LLM discoverability tracks traditional SEO signals (referring domains, community rank) more than novel AI tactics. Build the base first.
How the audit works
Three steps. No signup, no install.
1
Enter a URL
Type any public website. The engine fetches it server-side (no browser CORS limits), so it works on any site.
2
We score 13 dimensions
llms.txt, AI-crawler robots.txt, schema, query-shaped content, technical SEO, earned media, authority, E-E-A-T, content freshness, entity grounding, passage readiness, HTTPS cert health and GEO citation signals (statistics, quotations, source citations) — weighted by the research.
3
Get a fix list
A prioritized HIGH→LOW loophole report you (or we) can act on to become citable by AI search.
Pricing
Start free. When you want the score turned into citations, we do the work.
All prices in KES, VAT inclusive. Pay via M-Pesa, card, bank transfer or installments. Custom enterprise/white-label plans on request.
FAQ
Is the audit really free?
Yes. No signup, no credit card. The tool runs server-side and returns a full report. (White-label it for your own clients anytime.)
Can it audit any website, not just mine?
Yes — it fetches any public URL. Great for competitive research or prospecting.
Why does it check llms.txt and robots.txt?
llms.txt is the emerging machine-readable context standard for LLMs; robots.txt reveals whether AI crawlers (GPTBot, ClaudeBot, PerplexityBot) are explicitly allowed. Both are direct AEO signals.
Does a high score guarantee AI citations?
No tool can guarantee a citation — live presence in ChatGPT/Perplexity depends on many factors. The score measures readiness against the published evidence hierarchy so you fix the highest-leverage gaps first.
Will Kavenacc fix the issues for me?
Yes. Kavenacc builds AEO-ready sites, llms.txt, AI-crawler robots.txt and FAQ schema as standard. Tap the WhatsApp button to start.