Maximem Synap
1 commentMaximem Synap is context management infrastructure for the AI agents organizations build. It provides persistent structured memory, anticipatory retrieval, entity resolution, and knowledge pipelines that operate across vector, graph, and file stores. Ingestion is async, extraction converts meaning into structure rather than raw text, and retrieval nets across all three stores with a P75 latency under 15ms. The team publishes open benchmarks: 92% LongMemEval, 93.2% LoCoMo accuracy. Free tier available with Get Started on the Synap dashboard. Built by the Maximem team and backed by NVIDIA Inception, Google for Startups, and Neo4j. The platform is distinct from Vity, Maximem's encrypted personal memory product.
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Most agent memory tools are wrappers around a vector store or a gated platform feature. Synap's claim is infrastructure you can use: it writes to vector, graph, and file storage at once, resolves entities automatically, and retrieves context while the conversation is still going, not when the agent asks.
I have not connected it to a live agent with real users yet. The open LongMemEval benchmark and the async ingestion pipeline are what I would verify first. The alternative is context windows that forget, or memory that blocks the agent on every turn.