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The company said its enrichment tools "turn the product information a brand already has into more robust, consistent data." The Feedonomics and BigCommerce tools both generate: product titles, descriptions, feature bullets, frequently asked questions (FAQs) and search engine optimization (SEO) metadata

Commerce has released two artificial intelligence tools to help merchants make their product catalogs ready for AI discovery.

It calls the tools Feedonomics Enrichment and BigCommerce Catalog Enrichment, noting that the capabilities serve both B2B and B2C merchants. Commerce described the tools as agentic commerce solutions, or its products and capabilities to help merchants prepare their product data for agentic AI discovery. The enrichment capabilities also help merchants connect AI tools to their business, enabling merchants to enable agentic shopping experiences, according to Commerce.

“AI agents can only answer questions about your products as well as your data allows,” said Sharon Gee, senior vice president of product for AI at Commerce, in an announcement. “Whether you’re a marketer driving AEO or a product leader building shopping agents, better data is the foundation for better agentic experiences. Feedonomics Enrichment and BigCommerce Catalog Enrichment give brands on any platform a data pipeline that lifts performance everywhere agents meet shoppers from Google to OpenAI and on their own sites and agents.”

The companies that come to Commerce are typically “deep in B2B and in enterprise retail,” Gee told Digital Commerce 360 separately. Consumers and B2B buyers are asking AI products to compare products, answer questions and — more recently — make purchases.

Commerce is the parent company of BigCommerce, Feedonomics, and Makeswift.

Retailers in the Top 2000 Database that used Commerce as their ecommerce platform in 2025 generated more than $538 billion in online sales that year. The Top 2000 Database is a market research tool tracking North America’s largest online retailers by their annual web sales. It also tracks the leading vendors those retailers use for their ecommerce technology stacks.

What Commerce’s AI product catalog enrichment tools do

Commerce said its enrichment tools “turn the product information a brand already has into more robust, consistent data.” The Feedonomics and BigCommerce tools both generate:

  • product titles
  • descriptions
  • feature bullets
  • frequently asked questions (FAQs)
  • search engine optimization (SEO) metadata

In addition, they produce facts, snippets and question-and-answer (Q&A) fields that generative AI platforms can use to interpret products. That process helps to determine what a product is, identify its target audience and determine its relevance to a user.

Commerce said the enrichment process creates complete records that give human shoppers and AI agents consistent details across storefronts, marketplaces, answer engines and other channels. It also removes the need for CSV exports and third-party tools, according to Commerce.

Gee offered the example that a retailer might need to translate its footwear catalog to 15 languages. It then needs to send each of those translations to:

  • Amazon
  • eBay
  • Google
  • Meta
  • TikTok
  • Walmart

Now, in addition, retailers also need to send those translations to answer engine channels such as ChatGPT, Claude, CoPilot, Gemini and Perplexity.

“You need to be able to have UCP support for each of them,” Gee said. “It’s a one-to-many problem — scale.”

The BigCommerce enrichment tool allows merchants to make self-serve enhancements to their product content. Meanwhile, the Feedonomics enrichment tool offers both self-manage and managed-service models.

How B2B companies are using Commerce

Merchants also go to Commerce because they want the technology and tooling for B2B as well as their B2C capabilities, Gee said.

She also noted that hybrid businesses — those selling both B2B and B2C — often need flexibility and composability in their technology stacks.

“It’s fairly trivial to sell things online anymore,” Gee said. “That’s a well-solved problem over the past two decades. There are many use cases that have not been solved well yet.”

One such problem is keying in manual purchase orders, which can have thousands of line items. Gee said an AI agent can complete that work in a “very short amount of time,” whereas it would take a human hours. Commerce’s Purchase Order Agent, she said, allows users to drag and drop a PDF into it. From there, the agent will automatically build a cart.

“Now those humans could get back to doing human work instead of rote, nasty data entry that is super manual that doesn’t actually add more value,” Gee said.

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