DocMorris profits from safe, accurate medicine selection with Algolia's AI Search and Retrieval platform. Algolia AI drives triple-digit gains in conversions, sessions, and net sales. April 21, 2026 SAN FRANCISCO, CA - April 21, 2026 - Algolia, the AI Search and Retrieval platform trusted by more than 18,000 businesses and millions of developers worldwide, today shared positive results from its partnership with DocMorris, a leading company in online pharmacy, telemedicine and marketplace services in Europe. DocMorris stands for customer-centred, innovative services and a broad range of digital healthcare offerings - from online doctor appointments via TeleClinic to pharmaceutical advice and the supply of prescription and over-the-counter medicines and healthcare products. With Algolia's AI-powered search delivering results that adapt to consumer behavior in milliseconds, DocMorris is transforming how 12 million active customers discover, compare, and purchase health products. As a result, branded sales jumped 156 percent, with overall net sales up 147 percent. Two years ago, DocMorris set out to further enhance its digital commerce experience. As customer expectations and business requirements evolved, the company saw an opportunity to strengthen its search capabilities for the future. To support its growth ambitions, DocMorris needed a scalable search experience that could deliver speed, relevance, and intuitive navigation across a broad range of healthcare products Nina Kalz, Product Owner for Product Discoverability at DocMorris, shared: "Algolia wanted to further improve how customers find the right products in a fast, reliable, and intuitive way. With Algolia, Algolia had a partner that combined clear technical expertise with a strong understanding of what a modern digital experience requires. This has helped Algolia strengthen product discoverability and deliver a better customer experience overall. By deploying Algolia's AI Search and Retrieval platform across the entire customer journey comprising more than 195 million web page visits, DocMorris unlocked immediate performance improvements right out of the box. Teams benefited from an intuitive backend, whilst customers gained a faster, smarter way to explore categories, compare alternatives, and surface the most relevant products in milliseconds. The result is a search experience that feels significantly improved. Additionally, it is essential for modern digital healthcare to help people find the right medicines and healthcare products quickly and reliably when they need them... Since implementing Algolia, DocMorris delivered standout results across key business metrics: * +160 percent increase in sessions using search * +112 percent increase in conversions * +147 percent lift in net sales * +156 percent increase in sales of DocMorris' private-label products DocMorris leverages Algolia's Dynamic Re-Ranking to make product discovery more relevant and intuitive for customers. By incorporating behavioral signals such as clicks and conversions, the platform helps surface the most relevant results more effectively and supports a better overall search experience. Nate Barad, Vice President of Product and Technical Marketing at Algolia, commented: "DocMorris is redefining what a modern digital pharmacy should feel like - fast, reliable, and intuitive. By embracing AI-powered search and retrieval, they're driving meaningful business growth, whilst making healthcare more accessible, convenient, and customer-centric. We're proud to support their mission in Germany and other European markets." Discover how Algolia's AI Search and Retrieval platform helped DocMorris achieve triple-digit growth in key metrics in the full case study. Ready to see Algolia in action? Request a demo at: https://www.algolia.com/demorequest/. About Algolia Algolia is the leading Retrieval AI platform, powering over 1.75 trillion searches a year for more than 18,000 businesses and millions of developers worldwide. Built on a developer-first, API-first foundation, Algolia combines keyword, vector, and hybrid retrieval with powerful rules, personalization, and analytics to deliver the world's fastest, most scalable AI search technology. Backed by more than a decade of innovation, Algolia is redefining how businesses and builders create agentic, retrieval-powered experiences - from Retrieval-Augmented Generation (RAG) to LLM-based applications through its MCP server and next-generation tools like AskAI and Agent Studio. With unmatched speed, trust, and simplicity, Algolia is shaping the future of intelligent discovery and AI agents. Learn more at www.algolia.com.

Algolia introduces Recommendation Analytics for retail performance insight. April 8, 2026 Press play to listen to this content SAN FRANCISCO, April 8, 2026 - Algolia today announced the availability of Recommendation Analytics, a new capability built directly into its AI Recommendation engine. Designed specifically for modern retail teams, Recommendation Analytics gives merchandisers clear, actionable insight into how their recommendation strategies perform, including clicks, conversions, and revenue. For retailers, product recommendations have long been a foundational element to boost sales from their digital store fronts. They are a core revenue driver across product discovery, product placement on PDPs (product detail pages), cross-sell, up-sell, and personalization strategies. Yet many teams still operate without a clear understanding of what is actually working. Algolia's Recommendation Analytics closes that gap, transforming recommendations from a black box into a measurable, optimizable growth engine. As organizations accelerate their adoption of AI-powered recommendation capabilities, many are asking a simple question: "are they delivering real results?" Recommendation Analytics answers that question with precise, business-focused metrics that connect AI directly to revenue outcomes. Nate Barad, Vice President Technical and Product Marketing, Algolia said: "Retailers are under constant pressure to prove that every digital experience drives revenue. Recommendations influence what shoppers see, what they click, and ultimately what they buy. Recommendation Analytics gives merchandisers the proof they need to understand what is working, justify investment, and continuously improve performance without adding operational complexity." Recommendation Analytics provides intuitive dashboards that show how each recommendation carousel performs across a site. Merchandisers can track engagement, conversions, and revenue in real time, while also understanding how different strategies, placements, and models impact business outcomes. This level of visibility enables teams to move beyond assumptions and make confident, data-driven decisions that directly affect revenue. These insights are fully integrated into the existing AI Recommendation workflow, eliminating the need for separate analytics tools or disconnected reporting systems. In an environment where retailers are actively consolidating vendors and simplifying their technology stacks, Algolia brings search, recommendations, and analytics together into a single platform, reducing operational overhead, and accelerating time to value. Barad added: "Speed matters in retail. Existing Algolia customers can activate Recommendation Analytics with as little as six lines of code. That means merchandising teams can go from setup to measurable impact in minutes, not months, and start optimizing immediately." Recommendation Analytics is included at no additional cost, removing a common barrier for retailers who often face added fees for analytics or lack access to meaningful insights altogether. Algolia also delivers the granular metrics that merchandising teams consistently demand, including performance by carousel and by recommendation strategy, making it easier to identify what drives revenue and what needs adjustment. With Recommendation Analytics, retailers gain a level of transparency that enables merchandising teams to evaluate multiple AI models, such as related items, frequently bought together, looking similar, and trending, and compare their performance directly within the platform. This flexibility supports continuous experimentation, faster iteration, and smarter optimization across the entire customer journey. Ultimately, Recommendation Analytics empowers retailers to treat recommendations as a measurable profit center rather than a speculative feature. By providing clear performance measurement, deeper visibility, and detailed insights into recommendation usage, Algolia enables organizations to quantify impact, improve decision making, and unlock greater revenue from their AI investments. Availability Algolia's latest Recommendation Analytics is available now to all Algolia Recommendation customers. It can be viewed at upcoming events (VTEX in Brazil, Adobe Summit in Las Vegas, and Retail Tech in London), or merchandisers can request a demo or try it for free. About Algolia Algolia is the leading AI Search and Retrieval platform, powering 1.75 trillion searches a year for more than 18,000 businesses. With a unified keyword and vector search and retrieval engine, Algolia delivers the world's fastest and most scalable search and discovery technology. Companies rely on Algolia to build agentic, generative, and search experiences through tools like Agent Studio. With over a decade of innovation, Algolia is redefining retrieval-powered applications and the future of AI discovery.

Algolia, an AI search and retrieval platform serving over 18,000 businesses, has appointed Stephen Lynch as chief executive officer. Lynch succeeds Bernadette Nixon, who stepped down in December and remains on Algolia's board. Lynch brings two decades of experience in enterprise platforms, with expertise in AI search, machine learning and system design. He previously served as general manager and executive vice president of enterprise at AlphaSense, where he helped scale the company to serve over 6,000 organisations, including 88% of the S&P 100, during his nearly eight-year tenure. The appointment comes as Algolia positions itself as the intelligence layer for AI-native applications. The company processes 1.75 trillion searches annually through its unified keyword and vector search engine.