White-Label AEO/GEO Audits: What It Takes to Sell Them to Your Clients

Your clients are already asking

"Do we show up in ChatGPT?" More and more clients ask their SEO agency this question — and more and more agencies have nothing to answer with beyond an impression. No score, no proof, no costed action plan. Just "we'll look into it."

The problem isn't willingness. It's the absence of tooling to answer seriously : building a schema scanner, an llms.txt checker and an AI-agent tester in-house is months of development for an agency whose actual job is something else.

What an AEO/GEO audit actually needs to check

A sellable audit isn't a 40-page PDF full of generalities. It answers four precise questions, in order :

• Can the AI agent even get in? GPTBot, ClaudeBot, PerplexityBot, Google-Extended : each crawler has its own user-agent, and a misconfigured robots.txt — or a CDN silently blocking it — is enough to shut the door without anyone noticing.
• Does it understand what it reads? An up-to-date /llms.txt and complete schema.org markup (contact details, pricing, FAQ) give the agent a structured version of the site, instead of leaving it to guess from generic HTML.
• Is the site telling the truth? A wrong address or wrong hours in the published schema isn't a minor detail : one in three local AI recommendations contains a wrong contact detail (SOCi 2026 study — 350,000+ locations, 2,751 brands, US data, no comparable European study yet, but the signal is clear). A serious audit compares what the site actually publishes against what it should.
• Does a real agent find the answer? This is the question almost nobody tests. A site can be crawlable, well-marked-up, with accurate contact details — and an agent can still fail to find a room price because the information is poorly worded or buried three clicks deep.

The first three points can be checked with a static audit. The fourth requires sending a real agent with a real task and watching whether it succeeds — the full breakdown of the 3 levels is here.

Proof, not a declaration

A static score says "your schema is present, your llms.txt exists." It doesn't say whether an agent, faced with a real customer question, gets the right answer. That's the difference between an audit that reassures and an audit that proves.

The method that produces real proof runs in four steps : a real agent gets the actual question, ten times, in a real browser ; after a fix, ten more times, on a frozen version of the site ; every answer is judged fact by fact by a model from a different provider than the agent being tested, so a model never grades its own homework ; and the fix gets re-verified every week, because a site that changes can silently break what worked yesterday. That's the method Livada AgentRadar runs, with a signed, chained, never-rewritten log.

Compose the stack instead of building it

Building all four pieces above in-house — a scanner, a schema comparator, an agent tester, a monitor — only makes sense if that's your actual business. For an SEO agency, the question isn't whether to build it. It's how to compose it.

Three layers, each with one job :

The free layer, to qualify a prospect. Livada Trace scans a site in 30 seconds, no signup : a score out of 100 based on 7 signals (AI-bot access included), plus — in one run — a first real agent pass that publishes the exact path it takes through the site. Enough to open a sales conversation with a number instead of an opinion.

The proof layer, to sell the engagement. AgentRadar turns that first signal into a verifiable case file : ten agent runs before the fix, ten after, judged by an independent AI, then monitored weekly. That file — dated, numbered, signed — is what justifies an invoice, not a feeling.

The fix layer, to deliver. Once the gaps are identified, someone has to close them. On a WordPress site with admin access, Livada SEO fixes them natively : schemas, /llms.txt, and a live diagnostic that tests real access for 33 AI bots (actual HTTP status codes, not a guess). On a non-WordPress site — custom-built, static, hand-built — where no plugin can be installed, Livada Edge SEO injects the same signals in front of the site through a simple DNS record, without touching the CMS.

Sell it under your own name

A white-label audit carrying someone else's logo doesn't sell well — it just reminds the client they could go straight to the vendor. AgentRadar is built on the opposite principle : "Verified by Livada," never "Powered by." The report carries the agency's name ; Livada stays the independent verification seal, not a brand replacing yours.

The same logic applies to the fix layer : Livada SEO's Agency plan (50 sites) includes white-label on request. On Edge SEO, an agency manages its whole portfolio from one console, with access walled off per agency — each agency only sees its own sites.

The economics, plainly

On Edge SEO, wholesale pricing tapers with volume : 59 €/site/month for 1 to 9 sites, 39 € for 10 to 29 sites (the most-chosen tier, with white-label on request and a dedicated agency account), 25 € from 30 sites up. The suggested resale price is 79 to 149 €/site : on a 20-site portfolio at the Pro tier — paying 39 €, reselling at 99 € — the product page states the example outright : about 14,400 € of margin a year.

AgentRadar applies the same agency logic : the same prices as a direct client (€149 for the first diagnostic, then €29 to €199/month depending on monitoring level), with −30% from 10 monitored sites.

Where to start

You don't need to sell a full audit on the first call. Run a prospect's site through Livada Trace — free, 30 seconds — and you already have a score and a real agent path to show. If the prospect signs, AgentRadar turns that first signal into sellable before/after proof. And once the contract is signed, Livada SEO or Livada Edge SEO — depending on whether the client runs WordPress or not — fixes what the audit found.