Algolia provides hosted search and discovery APIs as a software-as-a-service. It helps businesses build fast and relevant search experiences on their websites or apps by offering a managed API for indexing and querying data, as well as features like recommendations. Developers and product teams integrate Algolia’s API into their sites or apps; Algolia handles the infrastructure, scaling, and maintenance so customers don’t need to run their own search servers. The company differentiates itself through a ready-to-use, cloud-hosted search solution with strong documentation and support that makes it easy to implement and optimize search without building from scratch. Its goal is to help businesses deliver efficient, tailored search experiences at scale, improving user experience and conversion across industries such as e-commerce and media.
Company Size
501-1,000
Company Stage
Series D
Total Funding
$333.9M
Headquarters
San Francisco, California
Founded
2012
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Algolia launches production-grade MCP for agentic commerce. Developers can now connect ChatGPT, Claude, Gemini and custom AI apps to live product data without rebuilding retrieval for every framework. Algolia, the AI Search and Retrieval platform orchestrating more than 1.75 trillion queries each year, trusted by more than 18,000 businesses and used by millions of developers worldwide, announced the Algolia MCP Server, its application for accelerating the creation of AI agents, and optimizing agentic commerce experiences. As AI becomes the interface for commerce, developers face a fundamental challenge: Large Language Models (LLMs) can reason, but they cannot answer commerce questions without access to live product catalogs, pricing, inventory, merchandising rules and business context. Today, those integrations are often rebuilt for every model, framework and application. Algolia eliminates that work by exposing Algolia's commerce intelligence through a production-ready Model Context Protocol (MCP) foundation. Developers can connect any leading LLM (including ChatGPT, Claude, Gemini) and MCP-compatible agent frameworks to trusted product search and retrieval without rebuilding retrieval infrastructure for every AI experience. At the core of the release is Algolia's MCP Server, which exposes product search, facet discovery, catalog context and retrieval as standardized AI tools. The same MCP foundation powers both Agent Studio and direct MCP integrations across chat experiences, search, and agent experiences. AI-generated index descriptions further help LLMs determine which catalogs to query and when to query them, which improves retrieval quality without additional developer effort. Stephen Lynch, Chief Executive Officer, Algolia, said: "AI is creating an entirely new interface for commerce. The companies that win won't be the ones building the best chatbot, rather they'll be the ones exposing trusted commerce intelligence to every AI agent, application and customer touchpoint. Agent Studio gives developers that foundation through MCP, making it possible to build once and extend intelligent commerce anywhere." Unlike generic LLMs, Algolia MCP gives AI agents access to that same live commerce data in production, including pricing, inventory, relevance, and merchandising rules rather than recreating those integrations for every framework or application. Developers can expose a single trusted commerce foundation that works consistently across the rapidly expanding ecosystem of AI agents. The latest release focuses on three developer priorities: a production-ready MCP foundation, a build-once deployment model across every commerce surface and production-grade controls for running AI agents safely at scale. A Production-Ready MCP Foundation for AI Agents Algolia's MCP Server turns Algolia's retrieval engine into a reusable foundation that AI agents can consume directly. Product search, facet discovery, relevance signals and catalog context become standardized tools that can be used consistently across ChatGPT, Claude, Gemini, custom applications or any framework that supports the MCP. The result is a portable discovery layer for AI commerce that powers conversational shopping, AI search and guided selling, without duplicating business logic or retrieval infrastructure. Build Once. Deploy Across Every Commerce Surface Agent Studio provides developers with the components, SDKs and deployment path needed to move from prototype to production quickly. A redesigned Quick Setup experience in the dashboard guides developers through connecting a catalog, configuring system prompts, enabling MCP tools, defining agent behavior and establishing safety policies. Once configured, Agent Studio generates production-ready implementation code, allowing teams to deploy their first AI experience in minutes rather than weeks. Developers can then embed the same AI capabilities across every customer touchpoint using Algolia's UI SDK, including search bars, autocomplete, chat, product pages, mobile applications and custom storefront experiences. AI-powered search becomes another interface to the same retrieval foundation rather than a separate application, which allows teams to extend identical product intelligence across every surface. Prompt suggestions, conversational entry points and agent behavior remain fully configurable, which provides developers control over how AI interactions begin and evolve without requiring application-specific implementations. Because the retrieval layer is shared through MCP, the same commerce intelligence extends beyond storefront experiences to external AI clients and agent frameworks ensuring catalogs are available wherever customers choose to interact with AI. Production controls for AI Agents Agent Studio provides the operational controls developers need to run AI-powered commerce applications with confidence. Guardrails, governance policies and cost controls can be configured independently for every agent without requiring custom infrastructure or middleware. Developers can define input and output guardrails, restrict disallowed content categories, configure fallback behaviors and enforce moderation before responses reach end users. For streamed interactions, responses are evaluated before presentation, preserving the responsiveness users expect while ensuring generated content complies with organizational policies. Operational controls extend beyond safety. Teams can configure request limits, per-IP rate limiting, maximum token budgets, conversation depth, tool execution limits, approved domains and other production boundaries that help control costs, reduce abuse and ensure predictable agent behavior at scale. Together, these updates make Agent Studio more than an interface for building AI commerce experiences, they make it the production infrastructure for exposing trusted commerce intelligence to modern AI systems. For developers, this means moving beyond isolated AI experiments and toward commerce applications that scale safely across every model, framework and customer touchpoint.
From Search & Discovery to agentic commerce experience. Algolia is pushing Search & Discovery forward with increasingly sophisticated AI. Bayezon changes the architecture. Product Intelligence understands the products. Intent Intelligence understands the shopper's objective. Agentic Search determines how to fulfill it. Journey Optimization determines what should happen next. Agentic Storefront(TM) turns those decisions into the experience. Algolia is evolving Search & Discovery. Bayezon is creating the step change to Agentic Commerce Experience. Don't just make Search & Discovery more intelligent. Make the entire commerce experience agentic.
Algolia names Chung & Servantez to AI growth roles. Thu, 10th Sep 2026 (Today) Algolia has appointed Steven Chung as Chief Revenue Officer and Veronica Servantez as Chief Marketing Officer as it expands beyond search into software that links AI agents with company data. London-based Chung joins from Starburst, where he was President and oversaw sales, marketing, professional services, channels, partnerships, support and revenue operations. Servantez joins from Genesys, where she was Senior Vice President of Product Marketing and led global go-to-market work across product marketing, content, thought leadership and analyst relations. The appointments add two senior executives as Algolia seeks to broaden its role in what it calls retrieval intelligence, focused on connecting business data, rules and permissions to search systems, recommendation tools, applications and AI agents. The push builds on a business that says it already handles nearly two trillion queries a year for more than 18,000 customers. According to Algolia, companies adopting AI agents often find the main challenge is not the model itself, but connecting it to internal data and controls quickly enough for practical use. Chung will lead Algolia's global revenue organisation, including expansion across EMEA and APAC, and work with cloud providers and systems integrators such as AWS, Google Cloud and Azure. Before Starburst, Chung held senior roles at BigCommerce, Delphix, PagerDuty and Demandware. His background includes guiding companies through periods of growth and acquisitions, as well as public market milestones, according to Algolia. Servantez will oversee Algolia's global marketing organisation and market positioning as it broadens its enterprise AI business. Her remit includes building awareness among enterprise and technical buyers and strengthening the company's case with analysts, developers and customers. Earlier in her career, she spent six years at BigCommerce, where she was General Manager of Small Business and later Senior Vice President of Marketing, leading an 80-person global team. She also held roles at Rackspace, where she worked on go-to-market strategy for managed public cloud products across AWS, Azure, Google Cloud and Alibaba Cloud. Stephen Lynch, Chief Executive Officer of Algolia, said: "Every retailer, marketplace and media company is putting agents into production - agents that shop the catalog, answer the customer, and cue up the next viewing - and most are stuck in the same place: the agent can reason, but it can't be trusted with the pricing, the merchandising or the brand. Veronica has defined new categories and built brands that moved markets. Steven has taken four companies from strong product to durable business, twice through an exit. They are proven operators for exactly this moment: taking the intelligence layer we've already built to every enterprise that needs AI it can govern, trust and measure." Growth plans Algolia has long been associated with search and product discovery tools used by retailers, marketplaces and media groups. It is now positioning itself more broadly around systems that help businesses deliver verified responses and recommendations to both people and software agents. In practice, that means using product, content and behavioural data to guide search rankings, recommendations and generated answers while applying business rules and evidence. Algolia argues this approach matters as businesses look to use AI agents in customer service, commerce and media environments where pricing, merchandising and brand controls remain sensitive. Servantez said the opportunity lies in presenting Algolia's work as broader than search. "This is an incredible time to join Algolia. Search is now becoming an entry point. What Algolia has built is an intelligent retrieval and context layer at scale which any site or AI application needs in order to deliver relevant, trusted and auditable results; the story is now much bigger than simply fast and reliable search. Very few companies get to redefine their category from a position of strength; Algolia has the technology, the reliability record and the customer base to do it. This is what excites me the most," Servantez said. For Chung, the task is to turn that positioning into larger enterprise deals across sectors where discovery and recommendations influence revenue. Those sectors include online retail, marketplaces and media, where search and recommendation tools often sit close to customer spending decisions. "I've watched several markets go through the same transition, where customers stop paying for a feature and start paying for a platform that drives strategic business value. Algolia is at that point. We deliver millisecond search and retrieval for more than 18,000 customers running mission-critical systems across different industries, use cases, and regions. Our focus is to help our customers reimagine their respective businesses in today's agentic economy. I'm inspired by what Algolia has built and the opportunity to help accelerate the AI journey for our customers," Chung said.
A decade powering digital commerce, two operators for the next one - Algolia names Steven Chung CRO and Veronica Servantez CMO. Two enterprise software operators join to scale Algolia's shift from category-leading search to outcome-driven intelligence; the layer that turns intent into trusted, measurable outcomes for every customer, application and AI agent. September 9, 2026 SAN FRANCISCO - September 09, 2026 - Algolia, the AI Search and Retrieval platform, today appointed Steven Chung as Chief Revenue Officer (CRO) and Veronica Servantez as Chief Marketing Officer (CMO). Both join as the company pushes past the category it has led for a decade - AI Search - into outcome-driven, retrieval intelligence: the layer that turns a business's products, content and behavioral data into trusted context for every search, recommendation, application and AI agent. Algolia moves into that market from an unusually strong base. It already handles nearly two trillion queries a year for 18,000+ customers at millisecond latency and five-nines reliability, and has been named a Leader in the Gartner(R) Magic Quadrant(TM) for Search and Product Discovery three times. Its ambition now sits well outside the search box: to be the intelligence layer between enterprise data and every human, application and agent that queries it - understanding intent, ranking against business objectives, enforcing explicit business rules and grounding every answer in evidence - serving classic search UX, generative experiences and autonomous agents from a single foundation. That ambition lands on a live enterprise problem. Companies putting agents into production are finding the model is the easy part; the hard part is grounding it in their own data, rules and permissions fast enough to act on. Chung and Servantez are hired to take that solution to market. Stephen Lynch, Chief Executive Officer, Algolia, said: "Every retailer, marketplace and media company is putting agents into production - agents that shop the catalog, answer the customer, and cue up the next viewing - and most are stuck in the same place: the agent can reason, but it can't be trusted with the pricing, the merchandising or the brand. Veronica has defined new categories and built brands that moved markets. Steven has taken four companies from strong product to durable business, twice through an exit. They are proven operators for exactly this moment: taking the intelligence layer we've already built to every enterprise that needs AI it can govern, trust and measure." Veronica Servantez, Chief Marketing Officer Servantez joins from Genesys, where as SVP of Product Marketing she ran global go-to-market across product marketing, content, thought leadership and analyst relations for the leading AI-powered experience orchestration platform. Before Genesys she spent six years at BigCommerce, as General Manager of Small Business and ultimately as SVP of Marketing leading an 80-person global organization. During her tenure she built their SMB Business Unit, defining a new complex SMB market segment that delivered sustained growth and record 10x revenue gains. As SVP of Marketing she delivered a 30% year-over-year increase in mid-market revenue, notably the highest growth rate in the company. Earlier, across more than a decade at Rackspace, she led go-to-market for the managed public cloud portfolio spanning AWS, Azure, Google Cloud and Alibaba Cloud, and took its $120M Cloud Office business into a new market with 10x revenue growth with the launch of Office 365. As CMO, Servantez will lead Algolia's global marketing organization, with a focus on establishing Retrieval Intelligence as the category analysts name and enterprises budget. Her role is to sharpen the brand for enterprise and technical buyers, and build the analyst, developer and customer proof points that carry Algolia from category-leading search provider to the Retrieval Intelligence Platform for the Discovery Economy, which comprise the markets where revenue depends on matching intent to a large, fast-changing catalog. Veronica Servantez added: "This is an incredible time to join Algolia. Search is now becoming an entry point. What Algolia has built is an intelligent retrieval and context layer at scale which any site or AI application needs in order to deliver relevant, trusted and auditable results; the story is now much bigger than simply fast and reliable search. Very few companies get to redefine their category from a position of strength; Algolia has the technology, the reliability record and the customer base to do it. This is what excites me the most." Steven Chung, Chief Revenue Officer Chung, who is based in London, joins from Starburst, where as President he led worldwide go-to-market across sales, marketing, professional services, channels, partnerships, support and revenue operations. During his tenure Starburst crossed $100M in ARR with 40% year-over-year ARR growth, 130% net dollar retention and 70% growth in EMEA, propelled by enterprise AI deals. He was previously President of BigCommerce (NASDAQ: BIGC) and also Delphix, where he efficiently grew the business to $200M ARR resulting in the company's acquisition by Perforce. Earlier Steven led worldwide revenue at PagerDuty (NYSE: PD) from Series B through its $2.8B IPO in 2019 and worldwide sales at Demandware (NYSE: DWRE), a publicly-traded ecommerce company, which Salesforce acquired for $2.8B in 2016. As CRO, Chung will lead Algolia's global revenue organization, with a focus on scaling platform-level enterprise deals across the verticals where discovery drives revenue - expanding EMEA and APAC, and building out the hyperscaler and systems-integrator ecosystem, including AWS, Google Cloud, Azure and global SIs, through which large enterprise AI programs are bought. Steven added: "I've watched several markets go through the same transition, where customers stop paying for a feature and start paying for a platform that drives strategic business value. Algolia is at that point. We deliver millisecond search and retrieval for more than 18,000 customers running mission-critical systems across different industries, use cases, and regions. Our focus is to help our customers reimagine their respective businesses in today's agentic economy. I'm inspired by what Algolia has built and the opportunity to help accelerate the AI journey for our customers." 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. Learn more at www.algolia.com.
Algolia vs Pigment: Revenue, Funding & Team size compared. Algolia generates $100M in revenue; Pigment generates $100M. Algolia and Pigment are close to the same size by revenue. The table below compares Algolia and Pigment on funding, valuation, customers, team size and headquarters - every figure GetLatka has verified for each company. | Company | AlgoliaThis company | Pigment | | Revenue | $100M | $100M | | Valuation | $2.3B | $1B | | Funding raised | $334.2M | $453.9M | | Customers | 17K | Not disclosed | | Team size | 899 | 714 | | Growth | 33.3% | Not disclosed | | Founded | 2012 | 2019 | | HQ | San Francisco, United States | Paris, France | Want the full dataset? GetLatka tracks revenue, funding and team history for thousands of SaaS companies, with charts, growth rates and founder interviews. Algolia at a glance. Algolia generates $100M in revenue with 899 employees, headquartered in San Francisco, United States. * Revenue - $100M * Valuation - $2.3B * Funding - $334.2M * Customers - 17K * Team size - 899 * Founded - 2012 Algolia is owned by Algolia Inc., a privately held company headquartered in San Francisco, California, USA. Algolia is a search-as-a-service platform that enables developers to build fast, relevant, and intuitive search experiences for... Pigment at a glance. Pigment generates $100M in revenue with 714 employees, headquartered in Paris, France. * Revenue - $100M * Valuation - $1B * Funding - $453.9M * Team size - 714 * Founded - 2019 Pigment is a business forecasting platform. Other Algolia alternatives. Algolia competes with more than the companies on this page. Browse the full alternative lists to compare revenue, funding and team size across the category. Algolia vs Pigment: frequently asked questions. Is Algolia or Pigment bigger? Algolia is the bigger company by revenue, at $100M against $100M for Pigment. How much revenue does Algolia make? Algolia generates $100M in annual revenue with a team of 899. How much revenue does Pigment make? Pigment generates $100M in annual revenue with a team of 714. How much funding has Algolia raised? Algolia has raised $334.2M in total funding since it was founded in 2012. How much funding has Pigment raised? Pigment has raised $453.9M in total funding since it was founded in 2019.