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The DURTA™ framework


DURTA is the framework behind maesee. It breaks one big question, "Can AI find, understand and recommend my business?", into five dimensions that can be tested and scored.

The name stands for Discoverability, Understandability, Recommendation, Trustworthiness and Actionability. Each dimension answers a specific question about how AI systems deal with your business, and each is scored out of 20. Together, they produce an AI Distribution Score out of 100.

The guiding principle is that DURTA scores observed AI behaviour and evidence, not opinion. Every score traces back to something an AI model actually did when tested.

The five dimensions

Discoverability

Can AI find your business?

This looks at whether AI mentions you when someone asks about your category, whether you appear among the options it offers, and how visible you are compared with competitors. If AI does not surface your business in relevant conversations, nothing else can follow.

The question it answers: when someone asks AI for providers in your category, does your business appear?

Understandability

Can AI explain what you do accurately?

This looks at whether AI describes your products, your customers, your use cases and what makes you different correctly and consistently. Being found is not enough if AI then misrepresents what you do.

The question it answers: when AI describes your business, does it get it right?

Recommendation

Will AI recommend you in relevant situations?

This looks at whether AI suggests your business when a customer describes a need it should match, how strong the reasoning is, and how you fare against named competitors in those moments.

The question it answers: when a customer describes a need, does AI recommend your business as a suitable option?

Trustworthiness

Can AI trust the information available about you?

This looks at whether AI's statements about you are accurate, consistent and well supported, and whether it tends to invent claims because reliable information is missing. Low trust shows up as vague, hedged or inaccurate answers.

The question it answers: does AI have enough reliable information to speak confidently and accurately about your business?

Actionability

Can AI identify the next step for a customer?

This looks at whether AI can point a customer to the right next action, whether that is getting a quote, making contact or starting a purchase, and how clear your digital journey is. As AI systems begin to act on behalf of customers, this becomes increasingly important.

The question it answers: can AI understand what a customer should do next, and in future, help initiate that action?

How the score works

Each of the five dimensions is scored out of 20, giving a total AI Distribution Score out of 100. The dimensions are weighted equally, so no single area dominates the result.

Scores are calculated from observed evidence gathered during structured testing. maesee runs a defined prompt pack through selected named AI models, captures the responses and extracts the observable signals from them. A primary model produces the headline score; cross-model comparison shows how observed behaviour differs across the tested models.

A fixed set of scoring rules then turns that evidence into the dimension scores. AI helps gather and structure the evidence, but it does not decide your score. The rules do, which is what makes every score explainable and repeatable.

Why a framework, and not just a single number

A single visibility score would tell you where you stand, but not what to do about it. DURTA separates the question into five parts so the result points to action.

A business might be highly discoverable but poorly understood, or well understood but rarely recommended. Knowing which dimension is weak is what makes the diagnostic useful rather than just interesting.

Named, versioned and transparent

DURTA is a versioned framework. Every report states which version of the framework was used, which AI models were tested and which prompt pack was applied, so results can be compared fairly over time and the method is always clear.

The result is an indicator of AI visibility and recommendation readiness, based on repeatable testing. It is not a definitive measure of how every AI system everywhere will behave, and it is not a way to control what AI says.

It is a credible, evidence-based read on where you stand and what to improve.

If AI was asked about your business, what would it say?

maesee shows you where you stand, why, and what to do next.

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