Your offer has changed. The AI answer hasn’t.
Your services, markets or expertise have moved on, but potential buyers could still receive an outdated description.
Ekaterina Shalel · Founder of Legibi
See how AI presents your business. Decide what to improve.
We're building Legibi for independent professionals, founders and marketing teams who need to understand how AI presents their offer when a potential customer compares options or checks credibility.
We’re designing it to connect the answers and sources with clear priorities for your team.
Legibi is in development. Request early access to discuss availability and fit.
Does this sound familiar?
You’re mentioned. Another business is recommended.
You need to see how the options are presented and what evidence supports the recommendation.
You have a visibility report. Your team still needs a plan.
The next question is which information, page or claim deserves attention first.
How I approach it
Start with a buying situation that matters to the business. Preserve the answer and its visible sources. Record a mention, a shortlist appearance and an explicit recommendation separately.
Then compare what AI says with the actual offer and available evidence. Separate factual errors from possible explanations, and identify changes worth testing.
The output should make the next step clear: which claim to clarify, which page to update, what evidence to add and what to check again. That is the workflow we’re building into Legibi.
Why that matters commercially
Every change competes for your team’s time and budget. Before commissioning more content or another website rewrite, you need a reason to believe that work addresses the problem.
A documented review gives you something concrete to evaluate and act on. A follow-up check can show what changed. Recommendations, enquiries and sales remain separate outcomes to measure.
About me
I’m Ekaterina Shalel, founder of Legibi. My background spans running businesses and building AI products, including SKINBOT in beauty retail.
My focus now is making AI recommendation analysis useful to the people deciding what to change in a business. Here I share the method, research and documented observations behind that work.
The canonical definition of AI legibility is maintained on its own page.
See the work behind the approach
Explore how I define a test, preserve evidence and turn findings into priorities. Read the research on AI recommendations and what different measurements can tell a business.
Have a question your team needs to answer?
Explore Legibi and tell us what you want to understand. Availability, supported capabilities and any pricing will be discussed before you commit.
Looking for the existing personal audit? View its scope and availability.