How we help

Catalogs built
for AI agents.

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

Process

What we do

We identify gaps, prioritize fixes, and optimize for agent visibility using agent-simulated analysis.

01

Audit

We analyze and simulate your product feed across 250+ dimensions. Every SKU gets scored on agent-readiness using the same models agents use.

02

Diagnose

You get a prioritized breakdown: what's missing, what's weak, what's blocking visibility. We identify quick wins and structural issues, with specific recommendations for each SKU.

03

Optimize

We restructure your catalog for agent consumption — enriching content, fixing taxonomy, adding conversational context, validating attributes. This is where catalogs go from browsable to recommendable.

04

Connect

We help your optimized catalog connect to agentic commerce. Products become discoverable, searchable, and purchasable through AI agents.

Models

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 handle everything. Audit, optimization, protocol connection, ongoing monitoring. You get results without building internal capability.

Best for

  • Large catalogs (1,000+ SKUs)
  • Complex product data or missing attributes
  • Teams without dedicated data resources
  • Brands prioritizing speed to market

What it looks like

Your top-selling jacket has the title "Men's Waterproof Jacket - Black - XL." An agent asked "best rain jacket for commuting" never surfaces it — nothing in your data connects product to intent. After Carve, that same SKU has enriched attributes, conversational context, and use-case mapping. It surfaces for 3x more relevant agent queries. You see the lift in your dashboard within weeks.

Self-serve

Carve Platform

Access the platform directly. Run audits, track agent visibility, get SKU-level diagnostics, and optimize on your own timeline. Full transparency into what agents see and what needs fixing.

Best for

  • Teams with existing data/catalog workflows
  • Brands wanting full control and transparency
  • Ongoing monitoring and optimization
  • Multi-brand or agency use cases

What it looks like

You launch a new product line. Within days, you see exactly how AI surfaces are picking it up — which queries trigger it, how it's described, where competitors rank above you. You spot that ChatGPT is pulling the wrong material attribute from your feed. You flag it, fix it, and watch the visibility score climb. No guessing. No three-month delay before you notice.

Not sure which fits? Get in touch and we'll recommend the right approach based on your catalog, team, and timeline.

Outcomes

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.

Protocol connections

Direct integration with OpenAI ACP, Google UCP, and emerging agent commerce protocols.

Visibility metrics

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

Actionable diagnostics

SKU-level recommendations showing exactly what's missing, weak, or blocking agent recommendations.

Continuous optimization

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

Competitive edge

Early presence compounds. You're not just keeping up — you're building an advantage while others catch up.

Ready to make AI agents choose you?

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