Independent scan of your public storefront. StoreSteady records what ChatGPT, Claude, Gemini, and Perplexity see, say, and skip — then shows you the exact product, policy, and comparison gaps costing you recommendations.
Use a product, collection, or homepage URL. The teardown reads the public evidence available to AI agents.
The scan surfaces what the AI answers correctly, where it hesitates, and where it swaps in a competitor instead.
You get a practical order of operations for the product, policy, and comparison gaps that matter most.
A checklist can tell you what exists. A teardown shows how the storefront behaves when an AI agent tries to answer a real shopping question.
The teardown follows the questions, answers, and comparison moments that AI agents use, instead of reviewing the page in isolation.
If the model cannot verify policies, product facts, or comparison support, the teardown makes those gaps visible in one place.
The output separates the biggest blockers from the smaller cleanups so your team knows what to fix first.
Run the free teardown to see what AI shopping agents understand, miss, and trust on your storefront before you spend time rewriting it.
