/ FOR AGENCIES + CONSULTANTS

Audit 30 client sites in a morning,
not a fortnight.

Same 130-signal scanner that powers the £2 single-page report — wrapped in a public REST API with bearer-token auth, rate-limit headers, per-key audit trail, and a 250-scan monthly quota. Designed for the consultant who has 12 retainer clients and needs to ship weekly AEO updates on every one of them.

See the tier matrix

/ 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.

No AEO coverage at all

Ahrefs, Semrush, Sitebulb, Screaming Frog — none of them check whether ChatGPT, Claude, or Perplexity can cite your client. They check classic SEO, indexation, backlinks. Useful work, but none of it answers the question your clients ask in 2026: "Are we in AI Overviews? Are we cited by ChatGPT?"

We're not replacing Ahrefs. We're the AEO layer that sits alongside it — the thing your clients will be asking about by Q3 2026, that nobody else in your stack covers.

/ THE STUDIO WORKFLOW

Monday morning, 8 AM

A concrete operational walkthrough. Map your own client list onto this pattern.

  1. 01
    8:00

    Trigger the batch audit

    Cron / GitHub Action / Zapier — your choice. Loop your client URLs through POST /api/v1/scan with 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
  2. 02
    8:03

    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 £2 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},...}
  3. 03
    8:15

    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.

  4. 04
    8:30

    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 £79/mo Studio gets you

Public REST API

POST /api/v1/scan with a bearer token. Returns full ScanResult JSON. Same scanner the £2 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.

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:

Studio subscription£79 / month
= one client's manual AEO audit at £80/hr × 1 hour
= 8.5 minutes of your billable hourly rate at £80/hr × 250 scans
= 1.5 hours per month of one junior's time at £50/hr

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, and Perplexity can cite your client. Every weight is cited and re-reviewed every 90 days. No black-box scoring.

/ WHY US, NOT NEXT YEAR'S MOZ

Three things nobody else does

The only audit that measures whether ChatGPT, Claude, and Perplexity 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.

signal-rules.ts · Public methodology repo lands in v1.1

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.

corpus/ · Public methodology repo lands in v1.1

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.

audit-stale.ts + ci.yml · Public methodology repo lands in v1.1

/ 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.

Free scan first

250 scans / month · £79 / month · cancel any time