Brand Legibility Diagnostic
See how AI compares your company, and what is worth changing
I work with founders and marketing teams who need to understand what AI tells potential customers about their company, products or expertise. We start with the buying decisions that matter to your business and investigate the answers people could receive.
Discuss your company’s needs · Are you an independent specialist?
When this work is useful
- ChatGPT recommends competitors when someone asks about your category.
- AI describes your company incorrectly, uses outdated facts or confuses the founder with another business.
- You have visibility reports but still do not know what to change.
- You need to decide whether a one-time audit, specialist help or ongoing monitoring is worth buying.
What you receive
- AI answers to agreed questions your potential customers might ask.
- A comparison with competitors: who is recommended and how your company is described.
- A review of inaccurate or missing information, with clear limits on what we can verify.
- Recommended changes in priority order, with an explanation of why they matter.
- Original answers and sources so you can inspect the findings.
My role
I help you understand what these answers mean for your business and which changes your team can act on. I distinguish verified errors from possible explanations.
Scope before commitment
We agree the subjects, AI tools, interfaces, markets, languages, scenario set, deliverables, price and delivery date before work begins. The diagnostic is complete with the agreed findings and recommendations; implementation, publishing, monitoring and a follow-up test are separate options.
When a lighter approach is enough
If you only need to check a few questions and can keep reliable records yourself, a manual review may be enough. If the problem is falling sales or poor conversion, we first establish whether AI-assisted discovery is relevant; this audit does not replace customer research, analytics or product work.
For one independent specialist and one service, see the personal AI Legibility Audit. For a platform workspace, Legibi is in development with invite-only access; my advisory engagement is scoped separately.
How the review works
Full review protocol · Research example with the original answer. This is exploratory research, not proof of improved recommendations.
Choosing the right scope
When is a one-time audit enough?
The scope should follow the decision at hand. A focused audit can help clarify a specific problem, prepare for a launch or establish whether further work is worthwhile. Implementation and a follow-up test need an agreed scope. Further checks make sense when important scenarios continue to matter and the team is ready to act on the findings.
What does ongoing work involve?
Checking whether important changes have held, investigating meaningful shifts and deciding what to do next. That can include correcting outdated facts, reviewing a changed source or competitor, and testing an approved intervention. The frequency should reflect the stakes and pace of change. Rewriting content every month is not the goal.
Can you guarantee that AI will recommend us?
No. We can define relevant tests, document what appears, improve evidence and access, and check the result. We cannot control every model, source or personalized answer. A recommendation in a test is also different from an inquiry or a sale; business outcomes need their own evidence.
How will we know whether a change helped?
If you commission a follow-up test, we compare repeated observations using the same core scenarios and closely matched conditions, with a change log and failed attempts retained. Implementation and follow-up testing are separate from the initial diagnostic. A changed answer alone does not establish which change caused it.
Request a diagnostic
Tell me what you want to understand, which people or businesses to review, and the markets and languages that matter. We’ll agree on the scope before work begins.