ReFiBuy debuts platform to optimize catalog data for agentic commerce
ReFiBuy launched 'Build with ReFiBuy,' a developer API platform (early access Q3 2026) that optimizes product catalog data to appear in AI-powered shopping responses from ChatGPT, Gemini, Perplexity, Copilot, and Meta.ai. Targets merchants using Akeneo, Salsify, Shopify, and Salesforce Commerce Cloud.
Agentic commerce is creating a new discovery layer outside Amazon/Walmart search — brands that don't optimize catalog data for AI protocols (OpenAI's ACP, Google's UCP) risk being invisible when shoppers query ChatGPT or Gemini instead of searching a marketplace. Start auditing product attribute completeness and Q&A content now, before AI engines lock in coverage rankings.
This signals AI disruption to traditional marketplace search dominance — as ChatGPT and Gemini become shopping entry points, catalog quality outside Amazon/Walmart algorithms becomes a direct revenue lever, fragmenting where discovery (and ad spend) must compete.
Audit your catalog for attribute gaps today — products missing structured data (specs, Q&A, reviews) will score low on AI 'product card coverage' and lose position in ChatGPT/Gemini shopping responses before you even know the channel exists.
In the next 30 days, add a structured Q&A section to your top 20 SKUs' content feeds — ReFiBuy and both ACP/UCP specs treat Q&A as a direct ranking input for AI prompt responses.
Bottom Line
AI shopping agents rank your catalog now — unprepared sellers lose visibility before they notice.
Source Lens
Analyst Intelligence
Research or editorial analysis that adds market context beyond the official announcement.
Impact Level
medium
AI shopping agents rank your catalog now — unprepared sellers lose visibility before they notice.
Key Stat / Trigger
No single quantitative trigger surfaced in this report.
Focus on the operational implication, not just the headline.
Full Coverage
The year-old ecommerce technology startup ReFiBuy launched in 2025 with the company’s focus set on emerging opportunities in the world of agentic commerce.
Now, it is rolling out a developer platform that it specifically designed to help merchants update product data from their catalogs to appear and perform better in artificial intelligence (AI)-powered discovery experiences.
It will first offer the developer platform, which it calls Build with ReFiBuy, in an early access release, the company announced March 24. ReFiBuy geared toward the types of prompt responses delivered by OpenAI’s ChatGPT, Perplexity or Google’s Gemini. The digital toolset leverages ReFiBuy’s Commerce Intelligence Engine.
ReFiBuy’s announcement coincides with other news from ChatGPT, Walmart and Shopify about how retailers’ product catalogs will ultimately feed ChatGPT’s commerce-related prompt responses. What is the Build with ReFiBuy developer platform?
“ReFiBuy has always been about making AI-ready product intelligence accessible,” said Scot Wingo, CEO and co-founder of ReFiBuy. “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.”
ReFiBuy’s explanation of how its Commerce Intelligence Engine works | Image credit: ReFiBuy press release Currently, ReFiBuy’s Commerce Intelligence Engine targets three priority areas in its output. The company lists those as: Enrichment. Pulling catalog data and closing attribute gaps, while optimizing fields. Distribution.
Improving product data to flow to OpenAI’s Agentic Commerce Protocol (ACP), Google’s Universal Commerce Protocol (UCP) and elsewhere. Monitoring. Scoring SKU eligibility based on how products appear in AI experiences.
For ReFiBuy, this process is one of assessing “for every SKU you have, what percentage are correctly mapped to a product card,” Wingo explained, responding to questions from Digital Commerce 360. He refers to this as “product card coverage.” Next is ranking as high as possible among competitors.
“Once you have coverage, you are in the game, but what position are you on the offer card?” he assessed. “The obvious goal [is] to be No. 1 on the card.” What helps products to appear in AI prompt responses? “The way you improve your product card coverage and ownership is through improvements to the product catalog,” Wingo stated.
“If you do this across the five Agentic Commerce Engines (ChatGPT, Gemini, CoPilot, Perplexity, Meta. ai) then that’s a lot of improvement to begin with and a ‘good start.’ ” At ReFiBuy, he sees common solutions such as adding new details and context to existing attributes, as well as making sure product reviews are visible to AI platforms.
In the cases of Gemini (with the UCP) and ChatGPT (with the ACP), Wingo also noted that those systems within their data-feed specs the ability to build what Wingo refers to as “an unlimited” question-and-answer file. “We have found the Q+A to be a great way to give the engines your product-level storytelling,” he explained.
ReFiBuy expects to make Build with ReFiBuy available more generally in early access in Q3 2026. In the meantime, it has already opened a design partner program for teams that work with Akeneo, Salsify, Shopify, Salesforce Commerce Cloud and AI agent frameworks.
Editor’s note: ReFiBuy works with Digital Commerce 360 on the new AI Commerce rankings and associated data that is being published throughout 2026. Do you rank in our databases? Submit your data and we’ll see where you fit in our next ranking update. Sign up Stay on top of the latest developments in the online retail industry.
Sign up for a complimentary subscription to Digital Commerce 360 Retail News. Follow us on LinkedIn, TikTok, X (formerly Twitter), Facebook and YouTube. Be the first to know when Digital Commerce 360 publishes news content. FavoriteThe post ReFiBuy debuts platform to optimize catalog data for agentic commerce appeared first on Digital Commerce 360.
Original Source
This briefing is based on reporting from Digital Commerce 360. Use the original post for full primary-source context.
Style
Audience