ReFiBuy, the Agentic Commerce Optimization platform that turns product catalogs into infrastructure for AI shopping engines, today announced early access to Build with ReFiBuy, a developer platform that gives brands, retailers, partners, and developers access to its Commerce Intelligence Engine.
Available through REST API, MCP server, and CLI, the platform enables teams to evaluate, enrich, distribute, sync, and monitor product data across existing PIM, feed, and commerce workflows.
Product Data Is Becoming Commerce Infrastructure
Most product data was built for search engines and human browsers, not for the AI shopping engines increasingly shaping how products are discovered, compared, and purchased. When a shopper asks ChatGPT, Perplexity, or Google Gemini what to buy, those systems rely on structured product data to determine which products qualify and which ones surface.
For many commerce teams, improving product data is still a manual, multi-tool process. A merchandiser moves between a PIM, a spreadsheet, and a content tool, then hopes the result is good enough. At scale, that breaks down. Listings go live with missing attributes, inconsistent descriptions, and little optimization for how AI shopping engines actually evaluate products.
Increasingly, it is not just consumers asking the questions. Autonomous shopping agents, commerce copilots, and AI procurement tools are also making decisions programmatically, raising the standard for machine-readable catalog intelligence.
A Developer Platform for Catalog Intelligence
Build with ReFiBuy gives developers access to the same Commerce Intelligence Engine used by leading brands across beauty, fashion, and retail, organized into three core product areas:
- Enrichment (Ingest + Enrich): Pull catalog data from any source, close attribute gaps, and generate LLM-optimized titles, descriptions, and Q&A pairs — all aligned to your brand voice, with human-in-the-loop review or full automation.
- Distribution (Distribute + Sync): Deliver agentic-ready product data to shopping surfaces including OpenAI’s Agentic Commerce Protocol and Google’s UCP, then sync enriched attributes back to systems like PIMs and ERPs.
- Monitoring (Evaluate + Monitor): Score SKU eligibility across AI shopping engines, track visibility and competitive position, and surface actionable fixes when products fall short.
Rather than replacing the existing commerce stack, ReFiBuy is designed to make it smarter. The goal is not another system of record. It is catalog intelligence that operates inside the systems commerce teams already use.
ReFiBuy has always been about making AI-ready product intelligence accessible. Build with ReFiBuy is the next step. It gives teams API access to the intelligence they need to improve product data inside the systems they already use.
– Scot Wingo, CEO, ReFiBuy
Built for Commerce Teams, Partners, and Agent Builders
Build with ReFiBuy is designed for three core groups across the agentic commerce ecosystem:
- Brands and retailers that want to improve how their catalogs perform across AI shopping engines without rebuilding their commerce stack.
- Integration and PIM partners that want to embed ReFiBuy capabilities into implementations and deliver agentic-ready catalog workflows across multiple clients.
- Agent builders creating AI-native shopping experiences that need product intelligence as a callable tool inside shopping agents, commerce copilots, and procurement workflows.
Build with ReFiBuy is available in early access starting Q3 2026, with a design partner program now open for teams working with Akeneo, Salsify, Shopify, Salesforce Commerce Cloud, and AI agent frameworks.
