MAMehul
Arora

Case study / 01

AI visibility audit tool

Active product build

AEO Engine

RoleProduct direction · AI systems · full-stack build

StageActive product build

Position01 of 03

The premise

When a customer asks an AI for a recommendation, is your business even in the answer?

01 / The product

What it is,
without the pitch fog.

Generates real buyer questions, runs evidence-aware LLM research, and makes the answer landscape visible: who gets named, why, and what to fix.

02 / Product decisions

The choices that
shape the system.

  1. 01

    Make every visibility score traceable to the evidence behind it.

  2. 02

    Start from real buyer questions instead of a generic keyword list.

  3. 03

    Turn research into an ordered action list, not another dashboard to decode.

03 / Honest evidence

Where the work
actually stands.

Current outcome

A working decision system that converts a fuzzy AI-visibility question into evidence, competitive context, and concrete next moves.

What the build clarified

A visibility score only becomes useful when the evidence and the next action sit beside it.

Next experiment

Test the decision flow with real business questions and keep tightening evidence quality.