AI Search: the search primitive for your agents

AI Search, previously known as AutoRAG, serves as an efficient search solution for diverse agent needs, such as coding agents searching code repositories or support agents retrieving customer tickets and internal documents. The tool simplifies the complex task of building a search system by providing a plug-and-play option that includes a vector index, an indexing pipeline, and the ability to dynamically create instances for different agents. It supports hybrid search capabilities, combining semantic and keyword matching to deliver precise results by fusing vector search with BM25. AI Search comes with built-in storage and indexing, allowing users to upload files directly via API, and supports the creation of instances per agent or customer without requiring redeployment. In a practical application, such as customer support, it enables agents to efficiently search both shared product documentation and individual customer histories to resolve issues faster and avoid redundant solutions. The system is powered by tools such as Workers AI and allows for metadata attachment to enhance search rankings, enabling seamless, scalable, and context-rich information retrieval across various instances.