
AI search for B2B is the work of making a supplier legible to AI-led buyer research: clear entity definitions, structured product and capability data, and content that answers procurement questions directly. Done properly, ChatGPT, Perplexity and Gemini can state what you sell, who you serve and where you operate when a buyer asks, which is the minimum bar for making a shortlist.
B2B buying starts long before the first email. Procurement teams, founders and category managers now ask AI engines for supplier shortlists, capability comparisons and risk checks. By the time someone fills in your contact form, the research is done, and it was done by a machine reading your website.
Most B2B and wholesale sites are invisible to that research. Capabilities live in PDFs, pricing is hidden everywhere, and the site never plainly says who you serve, what you sell, and where you operate. AI engines can't recommend what they can't parse.
The unglamorous work that wins: making sure every engine can answer "who is this company, what do they sell, who do they serve, where do they operate" in one pass. Organization data, location coverage, category definitions.
Line sheets and PDFs are invisible. We restructure wholesale catalogs as data: products, specs, MOQs, lead times. If the store itself needs building, that's Shopify Plus B2B.
AI engines weight verifiable claims. Named clients, concrete outcomes, real certifications, published terms. We restructure your proof so it can be checked, because checkable gets cited.
The same prompt-level tracking we run for consumer brands, pointed at B2B research queries. Start with the AI Visibility Assessment to see your current position.
Insights into the current and future state of Shopify Plus commerce. Headless architecture, agentic commerce, integration strategy, and the engineering decisions behind stores that scale.
The engine underneath is the same one we run for consumer brands: AI Search for Ecommerce. Structured data, content architecture, monthly measurement. What changes is the query set and the proof that matters: B2B engines get asked about reliability, capacity and terms, not vibes.
If you're a platform or app selling into retailers rather than a brand selling products, that's a different discovery problem again, and it has its own solutions track. Ask us about retailer discovery.
AI search for B2B is the work of making a supplier visible and accurately described when buyers research with AI engines. It combines entity clarity (a plain statement of what you sell, who you serve and where you operate), structured product and capability data, and verifiable proof, so ChatGPT, Perplexity and Gemini can include you when they answer supplier questions.
Yes, and more than in consumer. B2B purchases are researched heavily before contact, and that research is moving to AI engines that summarise and shortlist. Long sales cycles now start with an answer you never saw being generated.
Plain statements of who you are, what you sell, who you serve and where you operate. Structured product and capability data. Verifiable claims: named clients, real numbers, checkable certifications. Vague positioning language gets skipped.
Usually, yes. AI engines favour checkable information, and "contact us for pricing" gives them nothing to cite. You don't need a full price list; published starting points, ranges or MOQs give engines something concrete without giving away your rate card.
Your wholesale store is the proof layer. A well-built Shopify Plus B2B store with structured catalogs and clear terms is readable by buyers and their AI alike. We build both sides.