Catalogs built
for AI agents.

We restructure product data so AI agents can find, understand, and choose your products.

How it works

Score your catalog across every major AI surface. See exactly what to fix — then let Carve fix it.

01

Audit

Connect your store and we ingest your full product feed. Every SKU is profiled against the attributes AI agents evaluate when making recommendations.

02

Analyze

Each product gets an agent-readiness score across ChatGPT, Gemini, Claude, and Perplexity. You see exactly what's missing, what's weak, and what's already working — per SKU, per surface.

03

Optimize

Carve generates prioritized fixes for each product: missing attributes, weak descriptions, taxonomy gaps, conversational context. Sorted by impact so you fix what matters first.

Ongoing

Agent behavior changes. Your scores update continuously, surfacing new opportunities as AI platforms evolve.

Two ways to work with us

Choose the model that fits your team, timeline, and catalog complexity.

Done for you

Carve as a service

We audit, optimize, and connect your catalog. You get results without building internal capability.

  • Large catalogs or complex product data
  • Teams without dedicated data resources
  • Speed to market
Self-serve

Carve Platform

Run audits, track agent visibility, and optimize on your own timeline. Full transparency into what agents see.

  • Teams with existing catalog workflows
  • Full control and transparency
  • Multi-brand or agency use cases

What you get

Regardless of which model you choose, these are the outcomes.

Agent-ready catalog

Products structured, enriched, and validated for AI consumption across all major platforms.

Visibility metrics

Track how often your products surface in agent responses, where you're winning, and where you're losing.

Continuous optimization

Agent behavior evolves. Your catalog does too, with ongoing monitoring and refinement as protocols change.

Ready to make AI agents choose you?

Start with a free audit or discuss your catalog with our team.