Maximem launches Synap, a high-speed memory and context infrastructure layer providing persistent, low-latency state for AI agents across frameworks.
Maximem Synap is an agentic context and memory infrastructure layer built to give AI agents persistent state across conversations without requiring manual vector database or ranker tuning. It automates entity resolution, temporal reasoning, and multi-level scoping while delivering sub-15ms P75 recall and leading scores on benchmarks like LongMemEval (92%) and LoCoMo (93.2%). With native support across 22 agent frameworks—including LangChain, LangGraph, and the Claude Agent SDK—Synap enables developers to plug in long-term memory via open-source SDKs backed by a managed cloud engine.
Turnkey memory layers are replacing ad-hoc vector retrieval pipelines as agents demand low-latency, stateful context without maintenance overhead.
• Sub-15ms P75 retrieval with strong benchmark scores (92% LongMemEval, 93.2% LoCoMo) makes it viable inside tight agent execution loops.
• Automated entity resolution and temporal reasoning address core RAG failure modes like stale facts and contradictory user preferences.
• Plug-and-play SDKs across 22 frameworks lower integration friction for teams building on LangChain, LangGraph, or Claude Agent SDK.
• Relying on a managed cloud service for context storage creates data privacy and vendor lock-in considerations for enterprise deployments.
DISCOVERED
1h ago
2026-09-24
PUBLISHED
6h ago
2026-09-24
RELEVANCE
AUTHOR
[REDACTED]
