Cognee provides an open-source memory engine designed to serve as the retrieval and reasoning layer for AI agents. Rather than relying solely on standard vector search, the platform converts unstructured data and database records into dynamic knowledge graphs. This infrastructure allows agents to maintain long-term context and execute multi-step tasks by navigating structured relationships between concepts. It integrates with orchestration frameworks such as CrewAI and developer tools like Cursor to provide the necessary context for agentic workflows.

Within the agent stack, Cognee operates as a middleware layer focused on context curation and session management. It addresses the reliability issues of basic Retrieval-Augmented Generation (RAG) by automating ontology mapping and using feedback loops to improve data retrieval over time. For developers, the platform simplifies the process of building agents that can update their own knowledge structures without manual intervention. By offering a system that integrates with various data warehouses and LLMs, Cognee is pushing for a standardized, graph-based approach to agent memory and information processing.