September 6, 2026 · 7 min read · by Aashirvad Kumar
Most of the AI shopping advice this year has been written for Shopify stores, which leaves BigCommerce merchants reading tips they cannot directly use. That gap closed at Commerce Live 2026, where BigCommerce, through its Feedonomics arm, shipped a service built specifically for this moment. BigCommerce Agentic Catalog Exports, or ACE, is a one-connection path that pushes your catalog out to the AI assistants where shoppers are increasingly starting their search, without you wiring up each one by hand.
It is a genuinely useful piece of plumbing. But plumbing only moves what you put through it, and ACE will surface your products exactly as well, or as poorly, as your underlying product data and images allow. Turning it on is the easy part. Being worth surfacing is the work.
Key takeaways
ACE is an enterprise service that prepares and delivers agent-ready product data to the AI shopping surfaces where discovery is moving. Announced at Commerce Live 2026 as part of a broader agentic stack, it takes the catalog you already maintain and formats and syndicates it for consumption by AI assistants, rather than only by traditional shopping channels. The idea is that you keep one clean source of product data and let ACE handle delivering it, in the right shape, to each destination, so a merchant is not building and maintaining a separate integration for every new assistant that appears.
The reach is the headline. Through ACE, a BigCommerce merchant's catalog can be delivered to the major agentic surfaces at once, reported to include OpenAI's ChatGPT, Google's Gemini surfaces, Microsoft Copilot, Perplexity and Amazon. That is the practical value: instead of chasing each platform's onboarding separately as it launches shopping features, you prepare your data once and ACE fans it out. For a mid-market or enterprise catalog, that consolidation is real time saved, and it front-runs surfaces that are still early enough that being present is itself an advantage.
ACE did not arrive alone. BigCommerce framed Commerce Live 2026 around a broader agentic stack, with the catalog syndication of ACE sitting alongside pieces aimed at the rest of the buying journey, including a storefront layer for AI agents and an agentic checkout kit, plus payment tie-ins. The strategic message is that the company is treating AI-driven discovery and agent-led buying as a full pipeline rather than a single bolt-on feature, and ACE is the front of that pipeline: the part that gets your products in front of the assistants in the first place. For a merchant the useful read is that catalog syndication is the entry point, and it is worth getting right before the later pieces matter, because none of the downstream machinery helps if the assistant never surfaces your product to begin with.
Here is the part that decides whether ACE does anything for you. Syndicating a thin or inconsistent catalog to five AI surfaces does not make you five times more discoverable, it makes the same gaps visible in five more places. Agentic surfaces choose what to show a shopper based on how complete, specific and trustworthy the product record is, so a catalog missing identifiers, attributes or accurate availability gets passed over no matter how many destinations it reaches. ACE solves distribution. It does not solve data quality, and data quality is what actually gets you surfaced once the distribution is in place. The winning approach is to treat the export as the last step, after the catalog itself is genuinely agent-ready.
This is also why ACE rewards the merchants who least need convincing to do the unglamorous work. A store with a dozen well-tended products can often reach the same surfaces through simpler feeds, so the value of ACE grows with catalog size and with how many destinations you would otherwise have to manage separately. If you are a mid-market or enterprise BigCommerce merchant weighing it, the deciding question is not whether the AI surfaces matter, since they increasingly do, but whether your catalog is complete and accurate enough that being syndicated widely helps you rather than exposes gaps in front of a larger audience. Fix the data first, and the reach turns into an asset instead of a magnifier of problems.
Images do two jobs in this pipeline, and both matter. First, the image is part of the record an assistant evaluates and displays, so a clear, accurate product photo helps you get chosen and shown well. Second, and more decisively, the image is what a shopper judges the moment the assistant surfaces you. Agentic discovery still ends with a human deciding, and that human looks at the picture first. A catalog syndicated everywhere with weak imagery is highly discoverable and poorly converting, which is the worst of both worlds because you paid the distribution cost without the payoff. Accurate, consistent product images are what convert the reach ACE gives you into actual clicks and orders.
It is worth stressing the consistency point specifically, because a syndicated catalog is judged as a set, not one product at a time. When an assistant lines your products up against competitors, a catalog where every image shares the same clean framing and lighting reads as a serious brand, while a patchwork of mismatched photos reads as an unreliable one, even when each individual picture is fine. Reach exposes that inconsistency to more shoppers, so the wider you syndicate, the more a coherent visual standard across the whole catalog pays off.
Before you lean on ACE, get the catalog into a state worth syndicating. A short checklist covers most of it:
ACE is one platform's answer to a change every platform is now reacting to: shopping discovery is fragmenting across AI assistants, and the merchants who prepare their product data for that world get surfaced while the rest quietly disappear from the new front doors. The distribution mechanics differ by platform, but the underlying requirement, a complete and accurate catalog with honest imagery, is the same everywhere. Our AI product photography covers the imagery half, keeping every product image accurate to what ships so the catalog ACE syndicates converts the shoppers it reaches, and if you also sell on Amazon, consistent Amazon product photography from the same source keeps one honest look across every surface your products land on.
ListingRVA keeps every product image accurate and consistent, so the catalog ACE pushes to AI surfaces earns the click. 50 free credits, no credit card.
Start free →ACE is a Feedonomics service, announced at Commerce Live 2026, that prepares and syndicates a BigCommerce merchant's product catalog to AI shopping surfaces, so merchants can be discovered by AI assistants from one connection rather than integrating each surface separately.
It is reported to deliver catalogs to major agentic surfaces including OpenAI's ChatGPT, Google's Gemini, Microsoft Copilot, Perplexity and Amazon, letting a merchant prepare data once and reach several destinations.
No. ACE handles distribution, not data quality. Assistants still choose what to surface based on how complete, specific and trustworthy each product record is, so a thin catalog gets passed over even when it is syndicated widely.
Yes. The image is part of the record an assistant evaluates and the thing a shopper judges first when surfaced. Accurate, clear product images are what convert the reach ACE provides into clicks and orders.
Get the catalog agent-ready first: complete attributes, valid identifiers, data that matches your storefront, and an accurate image on every product. Then syndicate, so the export amplifies strength rather than gaps.
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