SAN FRANCISCO, October 6, 2026 — Algolia, a leading Retrieval Intelligence platform handling nearly two trillion searches a year, today announced it has acquired Velou. The New York-based company uses multimodal AI to extract context-rich product data from catalog text and images,  powering customer-facing search results and experiences for more than 50 retail and premium brand enterprise customers.

With this acquisition, Velou adds a powerful new layer of intelligence to the Algolia platform, compounding Algolia’s search, behavioral and AI intelligence with years of retail-specific product understanding. For brands, that means more precise results, higher conversions and catalogs ready for AI-driven shopping, all through the APIs they already use. [Terms were not disclosed.]

Shoppers often search the way they talk, but most product listings describe items in just a few words. Someone looking for a "machine-washable navy midi dress for a fall wedding" may never see the right dress if its listing simply says "blue dress."

Velou adds that detail automatically, extracting specific, evidence-grounded attributes from product text and images against a curated retail taxonomy, so search and discovery perform out-of-the-box without months of manual tagging and merchandising rules. U.K. sportswear retailer Get The Label used Velou to add more than 190,000 product attributes over six months, and revenue from its site search rose 60%.

Stephen Lynch, Chief Executive Officer, Algolia, said: "Algolia won search on speed. The future of discovery will be won on intelligence, and Velou strengthens one of our most important inputs: a deep, structured understanding of the products themselves. In return, Velou gets nearly 2 trillion searches a year, the behavioral signal that comes with them and a platform where that knowledge can improve several customer experiences at once. An AI agent can only successfully recommend a product that the data accurately describes. Together, we make that data far richer."

Product intelligence also matters beyond the retailer’s site. Shoppers are increasingly starting their searches in ChatGPT, Microsoft Copilot, Muse and Google Gemini, and AI-referred traffic to U.S. retail sites rose 62% year over year in July, according to Adobe Analytics. Those agents don't browse pages; they read structured product data. If a detail isn’t accurately represented in that data, the product effectively doesn’t exist to agent shoppers. Products described in structured detail are the ones agents can successfully find and recommend.

Gavin Hewitt, Chief Executive Officer, Velou, added: "Shoppers feel frustration every time a specific, high-intent search comes back empty. The industry has spent years racing on retrieval, but the race that matters now is contextual and relevant product understanding. We have built one shared vocabulary that describes every product and understands every query, grounded in evidence and checked by people. Algolia puts that to work across thousands of live catalogs from day one."

Velou has spent eight years building a retail taxonomy and product graph, which is a structured map of how products, categories and attributes relate. Alongside it, Velou also built a multi-modal enrichment engine that reads product descriptions and photos to extract specific attributes, each tied to evidence in the source. At U.K. fashion retailer Everything5pounds, the number of attributes in the catalog grew more than 85%, and search conversions rose 33%. With this acquisition, these capabilities are added to the behavioral, retrieval and relevance signals the Algolia platform already uses.

The experience for Algolia customers will be seamless. The APIs, SDKs and integrations remain the same; what changes is the depth of intelligence underneath them. Algolia expects the added product understanding to improve results for long, specific queries, strengthen recommendations and reduce hand-written, manual merchandising rules. It should also help new products rank before they have click history and make catalogs agent-ready. Velou's team of six joins Algolia's team.

Heather Hershey, Senior Research Director, Digital Commerce & Agentic Commerce Strategies, IDC, noted: "Product data has long been treated as back-office plumbing. AI shopping agents change that, because they pick products based on what the data says, not how a page looks. Retailers whose catalogs carry specific, accurate attributes are the ones those agents will recommend. Pairing product enrichment with search at this scale reflects where the market is heading." 

About Algolia
Algolia is the retrieval intelligence layer that turns intent into trusted, decision-grade outcomes. Powering nearly 2 trillion queries a year for over 18,000 customers with millisecond latency and 99.999% reliability, we are the recognized leader for Search and Product Discovery by top industry analyst firms. The Algolia platform turns a company's products, content, and business rules into data that humans, applications and AI agents can act upon. The result is trusted customer experiences with stronger conversions for measurable business impact.