Maximem Synap is a memory and context management platform for AI agents launched by Maximem, with the core goal of solving the problem of AI agents "forgetting": repeatedly asking users for information they have already provided, recommending content users have already rejected, contradicting themselves across sessions, or cramming everything into the prompt to compensate for missing memory. Synap provides agents with persistent memory and proactive context management.
Purpose and Positioning Synap treats memory as a proactive context management problem, not merely a storage problem. It manages writes (deciding what to store), retrieval (presenting the right context at the right time, including anticipatory prefetching), entity resolution (automatically linking references such as "my manager," "Sarah," "Sarah Chen," and "SC" to the same person), time awareness (weighting recent context more heavily than stale context), and deliberate forgetting (handling retractions and contradictions, with changes not destroying old versions and memory remaining traceable).
Key Capabilities
- Memory layering: divided into the organizational layer (company knowledge such as policies, product facts, and pricing shared across users and tenants), the long-term layer (persisted across sessions and per person, the layer users mean when they say "it remembers me"), and the short-term layer (working memory for the current session). A request can only see its own layer and all layers above it, never downward and never laterally, ensuring tenant and personal isolation. It also supports custom layer structures of arbitrary depth.
- Two calls: send the conversation to Synap in real time, query known information before the agent replies, and return a short, ranked set of facts that can be placed directly into the prompt. Writes return immediately without blocking the agent.
- No setup required: no need to run your own vector database, build an extraction pipeline, tune a retrieval ranker, or write scoping logic.
- Integration methods: provides Python and TypeScript SDKs, a REST API usable from any language, a hosted MCP endpoint, and native support for 23 agent frameworks, including LangChain, LangGraph, LlamaIndex, OpenAI Agents, Pydantic AI, CrewAI, AutoGen, Google ADK, Haystack, Agno, Semantic Kernel, Microsoft Agent Framework, NeMo Agent Toolkit, LiveKit Agents, Pipecat, Claude Agent SDK, Mastra, Vercel AI SDK, Vercel eve, Strands Agents, CAMEL-AI, Smolagents, deepagents.
- Speed and cost: in-session retrieval is under 15ms at P75, suitable for voice scenarios; context is prefetched before the agent asks; compression preserves signal and discards noise, avoiding token cost inflation and quality degradation.
- Three-tier consolidation: lightweight tidying every few hours, deeper tidying once a day, and deep consolidation and deliberate forgetting during quiet periods.
- Benchmarks and evaluation: 92% on LongMemEval and 93.2% on LoCoMo, using public evaluation tools, the same hardware, prompts, and conversations, with public methodology and open-source evaluation tools that can be reproduced independently.
How to Use Sign in with Google or GitHub; the free tier requires no credit card. To get started, install the SDK and configure an API key; most developers can get it running within 5 minutes. The documentation site is docs.maximem.ai, containing quick start guides, SDK references, and integration examples for each framework. The open-source SDK and evaluation tools are located at https://github.com/maximem-ai/maximem_synap_sdk。
Applicable scenarios For conversational, voice, and workflow agents such as customer support and sales agents, voice concierges, medical assistants, and multi-agent workflows.
Security and limitations Data is encrypted at rest, with strict tenant isolation; the enterprise edition adds VPC and private deployment, SSO/SAML, configurable RBAC, custom SLAs, and supports BYOK. The managed cloud provides dashboards, analytics, and a free tier; the full stack can be self-hosted but requires your own support. Specific pricing beyond the free tier is not provided in this material.
