Neural Memory

Neural Memory is a plug-and-play memory layer for autonomous AI agents, giving them long-term, structured, and reasoned memory recall. Unlike conventional vector databases, it stores memories as interconnected neurons in a graph structure, allowing agents to recall and reason through explicit relationships (e.g., CAUSED_BY, LEADS_TO). It supports offline operation, cloud sync on user infrastructure, semantic memory recall, versioning, and seamless integration with popular agent platforms and IDEs. Suitable for AI tool developers and power users wanting robust, scalable, and private agent memory.