Benefit language with no factual backing
AI agents cannot recommend a vague promise. If the copy says premium, durable, or best without evidence, the model has nothing firm to retrieve, compare, or cite.
AI commerce readiness
Your products are already being read by AI. Most of them are being skipped.
AI Commerce Hub audits, scores, and rewrites your product descriptions so ChatGPT, Claude, Perplexity, and Gemini can find them, understand them, and recommend them.
Being read by these agents right now
Ch
ChatGPT
Cl
Claude
Pe
Perplexity
Ge
Gemini
The problem
The shift no one on your team has planned for
Missing technical attributes
Material, size, compatibility, use case, warranty, stock, variants, and constraints are not nice extras. They are the facts agents use to decide whether your product fits a buyer request.
Inconsistent terminology
If one page says vegan leather, another says synthetic leather, and another says faux leather, agents treat the catalog as less certain. Uncontrolled language creates retrieval drag.
How it works
01
Import your catalog
02
Get your AI Confidence Score
03
Rewrite with AI assistance
04
Track discoverability over time
47%
Average score improvement after first rewrite
Illustrative until real customer data is published.
6x
More structured product facts per page
Illustrative until real customer data is published.
28m
Typical audit-to-rewrite workflow
Illustrative until real customer data is published.
Six tools for AI-ready product pages
Audit
Score each product against the signals agents need before recommendation.
Rewrite
Turn weak copy into structured, evidence-backed product language.
Scanner
Find vague, risky, inconsistent, or unsupported terms.
Schema
Generate JSON-LD that matches the actual page facts.
FAQ
Create buyer questions that answer real decision blockers.
Query Test
Test whether your copy answers the prompts buyers ask agents.