/ FOR AGENCIES + CONSULTANTS
Audit 30 client sites in a morning,
not a fortnight.
Same 137-signal scanner that powers the £5 single-page report — wrapped in a public REST API with bearer-token auth, rate-limit headers, per-key audit trail, 250 scans / month, and a Citation Probe loop that measures whether ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, and Bing Copilot actually cite your client's site. Designed for the consultant with 12 retainer clients who needs to ship weekly AEO updates on every one.
/ THE AGENCY PROBLEM
Your AEO process today looks like this
Manual, per client
Open Google Rich Results Test. Run their homepage. Copy the schema gaps into a doc. Paste their robots.txt into a parser. Check which AI crawlers are blocked. Search GSC for indexation issues. Cross-reference Lighthouse. Re-format into the client deck. 90 minutes per site. £80 of your time. Repeat for 12 clients every Monday.
They measure. They don't fix.
Semrush, Ahrefs and the rest now bolt on AI-visibility tracking — a dashboard that tells you whether your client is already mentioned by ChatGPT or AI Overviews. Useful, but it's reporting, after the fact. None of them audit why you're not citable, hand you the copy-paste fix for each gap, or certify the result — the part your clients actually need done.
We're not replacing Ahrefs. We're the layer that turns "you're not cited" into here's exactly why, here's the fix, here's your certificate — the part nobody else in your stack does.
/ THE STUDIO WORKFLOW
Monday morning, 8 AM
A concrete operational walkthrough. Map your own client list onto this pattern.
- 018:00
Trigger the batch audit
Cron / GitHub Action / Zapier — your choice. Loop your client URLs through
POST /api/v1/scanwith your bearer token. Each scan takes 8-15 seconds; 12 sites runs in under 3 minutes serially, faster if you parallelise.for url in $(cat clients.txt); do curl -X POST https://aisearchready.io/api/v1/scan \ -H "Authorization: Bearer $STUDIO_KEY" \ -H "Content-Type: application/json" \ -d "{\"url\":\"$url\"}" \ > "reports/$(date +%F)/$(echo $url | sha1sum | cut -c1-8).json" done - 028:03
Each response is a full ScanResult
Scores, verdict, priority-grouped issues with fixCode + recommendation, peer benchmarks per sector, AI crawler audit, llms.txt validation, generated llms.txt sample for missing files. Same shape as the £5 single report.
Rate-limit headers tell you exactly how much quota is left:
HTTP/1.1 200 OK x-ratelimit-limit: 250 x-ratelimit-remaining: 161 x-ratelimit-reset: 2026-06-01T00:00:00.000Z {"scanId":"...","scores":{"classic":73,"ai":91,"overall":84},...} - 038:15
Pipe diffs into your client digest
Compare this week's JSON against last week's. New critical issues? New missing schema? Score drift > 3 points? Pipe deltas into your client's slack channel, weekly email digest, or Notion DB. The corpus benchmark data included in each response (
scan.peerStats) lets you tell each client where they sit against their sector median without you having to maintain that data yourself. - 048:30
Half a day saved, before your first meeting
What used to be 12 hours of manual auditing across your Monday/Tuesday is now a 30-minute review of the diffs the pipeline surfaced. The classic-SEO workflow you already do (Ahrefs, Semrush) stays unchanged — this is the AEO layer that sits alongside it.
/ IN THE BOX
What £199/mo Studio gets you
Citation Probe — the loop nobody else closes
20 realistic queries per site × 5 LLMs (ChatGPT / Claude / Perplexity / Gemini / Grok) with web_search enabled. Measure who actually cites your client vs the competition. Re-probe weekly to see the diff. The piece every other tool stops short of.
Public REST API
POST /api/v1/scan with a bearer token. Returns full ScanResult JSON. Same scanner the £5 single-page report runs.
API keys + audit trail
Create multiple keys (CI / staging / production). Hashed at rest. Per-key lastUsedAt timestamp. Soft-revoke any key — soft so the audit trail survives.
250 scans / month
Resets monthly UTC. X-RateLimit-Remaining header on every response so your pipeline can throttle cleanly. Need more? Email us.
1,500 probe credits / month
1 credit = 1 LLM call. Default monthly grant covers ~25 deep probes (60 credits each). Top up free-form any time — 8p per credit, no caps, no preset packs.
Render-mode opt-in
Pass renderJs: true to escalate JS-heavy SPA shells through a headless Chromium render before scanning. Catches SPAs that look empty to AI crawlers but render fine in browsers.
9-sector peer benchmarks
Every response includes peerStats — your score vs the median/p75 for the inferred sector. 50+ labelled real sites across blog, saas, news, health, community_qa, ecommerce, finance, government, local_business.
Audited rule registries
Every signal weight has a lastReviewed date, source URLs, and EVIDENCE/HEURISTIC/CORPUS-CALIBRATED rationale. Show your client work without making it up.
/ ROI MATH
The honest sums
We won't insult you with conjured numbers. Here's the math you can do on your own client list:
If you have ≥ 2 retainer clients on a monthly AEO audit, Studio pays for itself in week 1. Everything past that is margin.
/ HONESTY LAYER
What we're not
We're the AEO layer. Not an Ahrefs replacement. Keep what works.
- Not keyword research, rank tracking, or backlink analysis — you have Ahrefs / Semrush.
- Not a full-site crawler beyond 10 pages per Deep Audit — Screaming Frog desktop handles unlimited at £199/year.
- No white-label PDF generation yet — coming. For now, the JSON response is yours to embed in whatever Notion / Looker / Slack pipeline you already have.
- We are the only audit in 2026 that explicitly measures whether ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, and Bing Copilot can cite your client. Every weight is cited and re-reviewed every 90 days. No black-box scoring.
/ WHY IT HOLDS UP
Three things nobody else does
The only audit that measures whether ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, and Bing Copilot can cite your client. Each pillar below has a verifiable file path in the open repo — no "trust us" needed.
Cited weights
Every signal weight carries a source URL and EVIDENCE / HEURISTIC / CORPUS-CALIBRATED rationale. When a client asks "why is this -8?" you can answer in seconds. Nobody else shows their work.
Empirical calibration
A growing corpus of 50+ labelled real sites tells us which rules actually predict citation outcomes. Weights tune to the data over time — run `npm run corpus:stats` to reproduce the per-rule correlations.
90-day audit cycle
Every rule has a lastReviewed date. `npm run audit:stale` fails CI when anything crosses 90 days unverified. Google quietly deprecates schemas; bot operators rename UAs — without an audit cycle, your tool rots. Ours can't.
/ READY?
Start with one client this week
Pick your biggest retainer. Run a free single scan on their homepage. If the report surfaces anything you didn't already have on your roadmap, Studio costs less than the next two hours of your billable time.
250 scans / month · £199 / month · cancel any time