Agent Studio is a platform for building and launching intelligent agents grounded in live Algolia search data. It enables agentic experiences that are accurate, brand-safe, governed, and scalable by building directly on top of Algolia’s AI Retrieval Platform.

Agent Studio is retrieval-first, not model-first. Responses are grounded in live Algolia indices, merchandising, rules, and relevance stay centralized, governance and brand safety are stronger, and hallucinations are reduced compared to generic LLM-only agents.

Many agent frameworks are designed for experimentation and require teams to assemble retrieval, orchestration, governance, and infrastructure themselves. Agent Studio is designed for production from day one with a built-in retrieval layer, visual configuration, templates, and enterprise-scale infrastructure. Customers can still use external frameworks if they choose, and Algolia can act as the retrieval and control layer even when other frameworks are used. Some customers prefer LangChain for advanced experimentation such as multi-LLM testing, and the value of switching is not always obvious to those teams.

While many AI solutions can be helpful, they can "hallucinate" answers. Agent Studio prevents hallucinations because it uses your up-to-the-minute data. It retrieves information from your structured search index to augment its generated responses with that data, an approach appropriately called Retrieval Augmented Generation, or RAG. 

Yes. Agent Studio supports use cases across every industry—from SaaS and media to enterprise search and beyond—making it adaptable to virtually any AI agent need.

Agent Studio lets you use your preferred large language model (LLM) provider, with support for Anthropic, OpenAI, Azure OpenAI, Google Gemini, and OpenAI-compatible models. View the full list of supported models.

Choose a model based on your requirements like relevance, speed, and cost. Use the LLM Leaderboard to compare options and find what fits your use case.

Yes. Agents can access any data indexed in Algolia, including help docs, guides, and more.

Many LLMs and agentic solutions lack memory from session to session or query to query. Unlike those solutions, Algolia’s Agent Studio has a built-in memory function. User memory is an optional setting that lets an agent remember user preferences and past outcomes so responses can stay consistent across interactions. Our customers can use this feature to provide more personalized agentic conversations to their visitors and buyers.

Agent Studio uses your first-party data—such as search interactions, transaction history, and user behavior—to generate highly relevant, brand-specific responses. Unlike generic agent frameworks, it integrates this data directly from your Algolia indices, giving your agents context-aware intelligence out of the box.