We don't consult on AI. We build, deploy, and run three production-grade AI agents inside Intershop and across the platforms we serve. Each one solves a specific B2B problem, each one is measured by business outcomes, and each one integrates with DIAS on day one.
A maintenance technician looking at a worn boiler component, a distributor rep walking an end-customer's facility, a mobile buyer on site — they have a photo, not a part number. Traditional search fails because it depends on exact product names, attributes, or SKU formats the buyer doesn't know.
Our Image Search Agent lets the buyer snap a photo — or drag in any product image — and returns the exact, compatible, or visually similar SKUs from your catalog. Powered by vision-language models tuned on product imagery, it considers visual details and technical specifications rather than relying on text descriptions alone. Fully integrated into the PDP, the buyer can add the match directly to cart or to a quote.
Scaling SEO-optimized, content-rich product pages across thousands of SKUs is a major challenge — but it's essential if you want to rank, capture buyer intent, and feed marketplaces. Most teams can enrich 50 SKUs a week manually. That math doesn't work for a catalog of 70,000.
SEOAI automates keyword optimization, metadata creation, and content freshness across the entire catalog. It writes product titles, descriptions, meta tags, structured attributes, and schema — and keeps them current as your catalog changes. To start, you give it three inputs: Brand, Product Name, and Product Number. SEOAI does the rest — and its output is pushed into Intershop, your PIM, and, via your Where-to-Buy integration, into retailer and DTC channels.
B2B catalogs are uneven. Some SKUs have full descriptions and imagery; most don't. That inconsistency hurts search, hurts recommendations, and hurts conversion — because recommendation engines only work when the underlying product data is clean.
Our Product Enrichment + Recommendation Agent does two things in sequence. First, it enriches product data — attributes, relationships, hierarchies — so every SKU looks the same to search and merchandising. Then it powers cross-sell, upsell, and bundle recommendations — on PDP, in the cart, at checkout, and in post-purchase email — based on co-purchase patterns, product similarity, and account-level buying history.
The distance between an AI pilot and an AI program is how most commerce AI initiatives die. We build every agent to run inside the commerce platform — observable, versioned, fallback-safe, and tied to revenue metrics from day one. If an agent underperforms, the business sees it. If it wins, the business owns it. No black-box vendor dependency. No two-year pilot with no ROI.
Every prediction, every output, every edge case — logged and inspected by merch and engineering.
Model and prompt versions ship like any other release. Rollbacks in minutes, not weeks.
If the agent fails, the storefront still works. No dependency on a single model vendor.
Measured against conversion, AOV, and abandonment — not model-accuracy abstractions.
Our three production AI agents — Image Search, SEO at scale, and Enrichment & Recommendation — wired into Intershop and running on real B2B catalogs.
Our signature demo enriches fifty of your actual SKUs — titles, descriptions, meta tags, attributes, images — so you can see what modern B2B commerce, powered by AI, looks like on your data.