Is this a way to audit our agency?

It measures your brand's standing in AI answers. It makes no judgment about any partner's effort or quality. It works best when you share the baseline with your agency at the start, so both sides agree on where you began and what success should look like.

Can an agency buy this for a client?

Yes. Agencies can use it to give clients an independent baseline before a GEO or AEO engagement and a third-party reading of progress afterward. Results are private to whoever buys the check, so when an agency buys it, the agency receives the report.

When should we run the baseline, and when the re-run?

Run the baseline before the work starts, and the re-run once the initiative's changes are live.

How do we make sure the two reports are comparable?

Compare two reports that used the same scan setup, which each records in its Methodology footprint. The panel is pinned to dated model snapshots and a slice of questions is re-asked, so a re-scan measures movement in the models rather than drift in the method. A head-to-head difference too small to be real is marked "too close to call" rather than shown as a lead.

The results differ from our own customer research. Which is right?

Both can be. The check measures what AI tools believe your market looks like. Where their version differs from yours, their version is what buyers are being told, and that gap is often the most useful thing to fix.

Will you recommend a provider or sell us follow-up work?

No. We sell no content, link building, or GEO services. The Monday plan assigns tasks by role, so you can give it to anyone.

Independent measurement for GEO and AEO

A neutral before-and-after for your GEO and AEO work

Run the AI Readiness Check before an initiative starts and again after it ends, and see what moved in how AI assistants describe and recommend your brand. Pure Neo sells no GEO or AEO services, so we have nothing to gain from the result.

Configure your baseline check See a sample report

Checks start at $1,890. The configurator shows the exact price for your scope before you pay. Results stay private.

You're paying for AI visibility. Who measures whether it worked?

Your team or agency is working to get your brand into AI answers. New content goes live, product pages get structured data, and a few months later a report says the numbers are up.

That report usually comes from the people who planned and delivered the work. This is normal, since they know the work best. It still leaves questions that are hard to answer from inside the project:

Where exactly did we stand before we started?
Did the change come from our work, a model update, or one good day of search results?
Are the before and after readings measured the same way?
Did we gain ground, or did the whole category move?

The stakes go beyond one report. AI's version of your market is what buyers are told. Where it differs from what is true, or from your own research, the AI version wins over time.

You need a reading from someone outside the delivery, one you can put next to your partner's report and discuss on equal terms.

Delivery reports and quick checks answer different questions

Delivery reports are built to track the work: what shipped and when. Measuring the outcome of your own work with full neutrality is hard for anyone, however careful.

Many quick AI visibility checks run a small set of prompts once and return a single score. AI answers vary from run to run, so a single reading can move with nothing having changed. Live search results also change daily, for reasons unrelated to anything your team did.

Keep your partner and keep your tools. They do their jobs. The AI Readiness Check adds one thing they are not set up to provide: a repeatable measurement made by a party that sells none of the work.

Why Pure Neo has no stake in your result

Pure Neo sells no content, no link building, and no GEO or AEO services. A weak result does not turn into a sales pitch, and a strong one does not turn into a retainer.

The report ends with a Monday plan: one ranked to-do list, with each task assigned to an owner by role: whoever runs your website, owns your content, or owns your positioning. Hand it to your in-house team, your current agency, or a new one.

Finance teams bring in an outside auditor even when they trust their accountants. The same governance applies here: you and your partners work from one shared set of numbers, and the conversation moves to what to do next.

Been there, done that.

The check was built by a designer with two decades inside the SEO and content playbook for some of the biggest brands in the world. The playbook worked and still works. It also shaped the web AI learned from, and we now deal with its side effects.

Designed digital products for Allianz, MetLife, JPMorgan Chase, BlackRock, Nestlé and Porsche.

A baseline you can repeat and compare

A fixed panel of leading AI models is asked a large set of realistic buyer questions about your market. Each buyer need is asked in several phrasings, and a sample is deliberately re-asked. Every scan is built on 7,000+ analyzed data points. For a before-and-after comparison, three things matter most:

What the models hold, separate from live search. The check measures what the models themselves know about your brand and market, apart from what a web search returns on a given day. That is the layer behind the confident answers buyers get, and it does not swing with one day's search results.
Statistics with the scan results. The check uses statistics so that small differences are marked "Too close to call" rather than shown as a lead. The panel is pinned to dated model snapshots and a slice of questions is re-asked, so a re-scan measures movement in the models rather than drift in the method.
Named competitors. Add the competitors you track. The re-run shows whether you gained ground on them, so a general rise across your market is not mistaken for progress of your own.

A technical audit checks whether AI models can reach, read, and extract your website and product information: structured data, machine-readable specs, crawlability, and llms.txt (informational). Each failing check comes with fix text, so after the work you can confirm which fixes landed.

How it works

Configure your scope. Choose your market and add named competitors. For a before-and-after, note the scope so the re-run uses the same one. The comparison holds when both runs use the same scan setup (same model panel, question set and scoring version), and the report records that setup in its Methodology footprint.
See your price. Checks start at $1,890. The configurator calculates the exact price from your scope and shows it before you pay. Prices exclude VAT.
The scan runs. The model panel answers your buyer questions, and the technical audit checks your site.
Get your report and Monday plan. Share the plan with any team or agency. Once the initiative's changes are live, run the same scope again and compare the two reports.

A report where each section answers one question

For this use, these sections carry the comparison:

Verdict: Where do we stand overall? One readiness score with three pillar scores: your baseline now, your comparison point after the re-run.
Visibility map: Where do we show up in AI answers, and where don't we? The topics your initiative should move.
Who AI recommends instead of you. When you don't come up, you see which brands AI names instead, with each one's share of voice. Re-run it to see whether that changed.
Machine access: Can AI models read our website, and what do we fix first? A checklist your web team or agency can close.
Methodology footprint: How the scan was run. It records the pinned model snapshots and the scan setup, so you can confirm the re-run is comparable.
Monday plan: A ranked to-do list with owners and a link to the evidence for each task.

The report also covers the model split, whitespace topics no brand owns yet, and what AI says about you, laid out so you can hold each finding against reality.

Your results stay private. Pure Neo never publishes customer results. They belong to your brand, and you decide who sees them, including whether your agency gets the full report or only the Monday plan.

Questions

Is this a way to audit our agency?: It measures your brand's standing in AI answers. It makes no judgment about any partner's effort or quality. It works best when you share the baseline with your agency at the start, so both sides agree on where you began and what success should look like.
Can an agency buy this for a client?: Yes. Agencies can use it to give clients an independent baseline before a GEO or AEO engagement and a third-party reading of progress afterward. Results are private to whoever buys the check, so when an agency buys it, the agency receives the report.
When should we run the baseline, and when the re-run?: Run the baseline before the work starts, and the re-run once the initiative's changes are live.
How do we make sure the two reports are comparable?: Compare two reports that used the same scan setup, which each records in its Methodology footprint. The panel is pinned to dated model snapshots and a slice of questions is re-asked, so a re-scan measures movement in the models rather than drift in the method. A head-to-head difference too small to be real is marked "too close to call" rather than shown as a lead.
The results differ from our own customer research. Which is right?: Both can be. The check measures what AI tools believe your market looks like. Where their version differs from yours, their version is what buyers are being told, and that gap is often the most useful thing to fix.
Will you recommend a provider or sell us follow-up work?: No. We sell no content, link building, or GEO services. The Monday plan assigns tasks by role, so you can give it to anyone.

Set your baseline before the next initiative starts

Choose your scope. Checks start at $1,890. The configurator shows the exact price before you pay. When the work is done, run the same check again and see what moved.

Configure your baseline check

Questions before you buy? Email us