Agentic Context Management # Your AI Agents Forget.Synap Makes Them Remember. Persistent memory and context for AI agents, across all popular agent frameworks. [92%LongMemEval accuracy](https://www.maximem.ai/blog/maximem-synap-updates-higher-benchmark-scores-and-more)[93.2%LoCoMo accuracy](https://www.maximem.ai/blog/maximem-synap-updates-higher-benchmark-scores-and-more)[<15msP50 recall latency](https://www.maximem.ai/blog/maximem-synap-updates-higher-benchmark-scores-and-more) [Get Started Free](https://synap.maximem.ai)[See it in action](https://synap.maximem.ai/playground) No credit card required. Google or GitHub sign-in. [Read the docs →](https://docs.maximem.ai)[See all integrations →](https://www.maximem.ai/synap/integrations)[Synap SDK reference →](https://docs.maximem.ai/sdk/initialization)[View on GitHub →](https://github.com/maximem-ai/maximem_synap_sdk) Native integrations with [![LangChain](https://registry.npmmirror.com/@lobehub/icons-static-png/1.24.0/files/dark/langchain-color.png)LangChain](https://docs.maximem.ai/integrations/langchain)[![LangGraph](https://www.maximem.ai/assets/images/icons/frameworks/langgraph.svg)LangGraph](https://docs.maximem.ai/integrations/langgraph)[![LlamaIndex](https://www.llamaindex.ai/brand/llamaindex-logo-white.svg)LlamaIndex](https://docs.maximem.ai/integrations/llamaindex)[![OpenAI Agents](https://registry.npmmirror.com/@lobehub/icons-static-png/1.24.0/files/dark/openai.png)OpenAI Agents](https://docs.maximem.ai/integrations/openai-agents)[![Pydantic AI](https://pydantic.dev/docs/ai/img/pydantic-ai-light.svg)Pydantic AI](https://docs.maximem.ai/integrations/pydantic-ai)[![CrewAI](https://cdn.prod.website-files.com/69a111972d2e0bbcc6adb934/69a111972d2e0bbcc6adbbba_Logo.svg)CrewAI](https://docs.maximem.ai/integrations/crewai)[![AutoGen](https://www.ag2.ai/_next/image?url=%2Fag2-logo-black.png&w=256&q=75)AutoGen](https://docs.maximem.ai/integrations/autogen)[![Google ADK](https://storage.googleapis.com/gweb-developer-goog-blog-assets/images/ADK-512-color_banner.original.png)Google ADK](https://docs.maximem.ai/integrations/google-adk)[![Haystack](https://haystack.deepset.ai/images/logos/haystack.png)Haystack](https://docs.maximem.ai/integrations/haystack)[![Agno](https://www.maximem.ai/assets/images/icons/frameworks/agno.svg)Agno](https://docs.maximem.ai/integrations/agno)[![Semantic Kernel](https://registry.npmmirror.com/@lobehub/icons-static-png/1.24.0/files/dark/microsoft-color.png)Semantic Kernel](https://docs.maximem.ai/integrations/semantic-kernel)[![Microsoft Agent Framework](https://www.maximem.ai/assets/images/icons/frameworks/microsoft.png)Microsoft Agent Framework](https://docs.maximem.ai/integrations/microsoft-agent)[![NeMo Agent Toolkit](https://www.maximem.ai/assets/images/icons/frameworks/nvidia.svg)NeMo Agent Toolkit](https://docs.maximem.ai/integrations/nemo-agent-toolkit)[![LiveKit Agents](https://www.maximem.ai/assets/images/icons/frameworks/livekit.svg)LiveKit Agents](https://docs.maximem.ai/integrations/livekit-agents)[![Pipecat](https://www.maximem.ai/assets/images/icons/frameworks/pipecat.svg)Pipecat](https://docs.maximem.ai/integrations/pipecat)[![Claude Agent SDK](https://www.maximem.ai/assets/images/icons/frameworks/anthropic.svg)Claude Agent SDK](https://docs.maximem.ai/integrations/claude-agent)[![Mastra](https://www.maximem.ai/assets/images/icons/frameworks/mastra.svg)Mastra](https://docs.maximem.ai/integrations/mastra)[![Vercel AI SDK](https://www.maximem.ai/assets/images/icons/frameworks/vercel.svg)Vercel AI SDK](https://docs.maximem.ai/integrations/vercel-adk)[![Vercel eve](https://www.maximem.ai/assets/images/icons/frameworks/vercel.svg)Vercel eve](https://docs.maximem.ai/integrations/eve)[![Strands Agents](https://www.maximem.ai/assets/images/icons/frameworks/strands.svg)Strands Agents](https://docs.maximem.ai/integrations/strands-agents)[![CAMEL-AI](https://www.maximem.ai/assets/images/icons/frameworks/camel.png)CAMEL-AI](https://docs.maximem.ai/integrations/camel-ai)[![Smolagents](https://registry.npmmirror.com/@lobehub/icons-static-png/1.24.0/files/dark/huggingface.png)Smolagents](https://docs.maximem.ai/integrations/smolagents) [Synap memory for LangChain →](https://www.maximem.ai/blog/langchain-maximem-synap-memory-integration)[Synap memory for LangGraph →](https://www.maximem.ai/blog/langgraph-synap-memory-integration)[See all 22 integrations →](https://www.maximem.ai/synap/integrations) The thesis ## Memory is not a storage problem alone.It is an active context-management problem. Every other tool stores and retrieves. Synap actively manages context for your agent, per agent, per domain, per customer. 01/What you get ## What changes when your agent can actually remember ### Remembers every user - Recall across sessions, channels, and months, not just the last twenty turns - "Sarah," "Sarah Chen," and "SC" resolve to one person automatically Under the hood: structured capture and entity resolution. ### Remembers your organization - Shared policies, product knowledge, and team context for every agent that should see them - Isolated from the users and tenants that should not Under the hood: customer and client scopes. ### Without the token bill - Context stays lean as conversations grow, so cost does not balloon and quality does not rot - Compaction keeps the signal, drops the noise, and tells you when it worked Under the hood: validated compaction. ### Fast enough for voice - Context is pre-fetched before your agent asks, returning in 15ms at P50 - A voice agent stays conversational instead of pausing Under the hood: anticipatory retrieval. [See the memory problem in depth →](https://www.maximem.ai/the-memory-problem)[Why we built Synap →](https://www.maximem.ai/blog/why-we-built-synap)[How Synap works →](https://www.maximem.ai/blog/how-maximem-synap-works) 02/Not a vector database ## A vector database is not memory. Retrieval finds text that looks similar. Memory maintains what is true, current, and yours. You can bolt the missing pieces on one at a time, or you can use a system that was built to manage them together. The problem Vector DB / RAG alone What memory actually needs Provenance Returns matching text, no source Tracked origin per fact Stale data Stores everything forever Conscious forgetting and TTLs Duplication Near-duplicate chunks pile up Consolidation Meaning Similarity is not truth or state Structured facts, episodes, entities Entity resolution "Acme" and "Acme Corp" differ Resolution to one entity 03/How it works ## How Synap works A conversation turn does not land in a database. It runs through a pipeline that turns raw dialogue into structured, scoped memory, governed by an architecture generated for your specific agent. Scroll the diagram sideways to follow the full path → [See the full architecture →](https://www.maximem.ai/synap/how-it-works) 04/Inside Synap ## What makes it managed, not just stored MACA ### Custom architecture per agent - Generates a memory architecture for each agent from a use-case description - Manages and adapts it as the session grows, with no schema to hand-author Extraction ### Structured extraction and entity resolution - Raw text becomes facts, preferences, episodes, emotions, and temporal events - Mentions of one person or company collapse to a single entity; ambiguous matches go to a review queue, not a guess Compaction ### Validated compaction - Compaction is not summarization - Every pass returns a validation score and a preserved-facts count, so you know when compression kept the signal IACS ### Automated scoping - Memory is isolated across User, Customer, and Client, applied automatically - One user's memory never leaks into another's session, and shared knowledge stays shared Also built in Anticipatory pre-fetch at 15ms P50Temporal awarenessNative multi-agent context sharingFast and accurate retrieval modesVector, graph, and file stores 05/Scopes ## The right memory reaches the right tenant, and never leaks User to Customer to Client. When your agent handles a ticket from someone at Acme, it sees what you know about that user, about Acme, and about your product globally, ranked so the most specific answer wins. Client · your whole app Shared product knowledge, visible to everyone Customer · Acme Policies, team, and shared projects for this tenant User · Alice Facts, preferences, and episodes about this person private to Alice no leak Customer · Globex Policies, team, and shared projects for this tenant User · Bob Facts, preferences, and episodes about this person private to Bob A user's memory never leaks into another user's or another tenant's session, while organizational knowledge stays shared where it should be. Retrieval prefers the narrowest applicable scope. 06/Proof ## Highest accuracy, lowest latency, and you can check it yourself Synap scores 92% on LongMemEval, the benchmark that tests whether a memory system retrieves the right fact from a long conversation and holds that accuracy as the conversation grows. Retrieval is 15ms at P50. These numbers are a consequence of the architecture, not prompt tricks. The methodology is published and the eval harness is open source, so you can run it against any system you are evaluating. |   | Synap | Mem0 | Zep | Supermemory | | --- | --- | --- | --- | --- | | LongMemEval | 92% | 57.5% | 63.8% | 71.3% | | P50 retrieval latency | 15ms | 180ms | Not published | 220ms | | Entity resolution | Automatic, every tier | Pro tier only | Automatic | Fact extraction | | Open-source eval harness | Full config published | No | No | No | [Synap vs Mem0](https://www.maximem.ai/compare/maximem-synap-vs-mem0)[Synap vs Zep](https://www.maximem.ai/compare/maximem-synap-vs-zep)[Synap vs Letta](https://www.maximem.ai/compare/maximem-synap-vs-letta)[Synap vs Supermemory](https://www.maximem.ai/compare/maximem-synap-vs-supermemory)[Synap vs Cognee](https://www.maximem.ai/compare/maximem-synap-vs-cognee)[Synap vs Evermind](https://www.maximem.ai/compare/maximem-synap-vs-evermind) [See the full Synap vs Mem0 vs Zep vs Letta vs Supermemory vs Cognee vs Evermind comparison →](https://www.maximem.ai/compare/maximem-synap-vs-mem0-vs-zep-vs-letta-vs-supermemory-vs-cognee-vs-evermind) 07/Where it runs ## Works across conversational, voice, and workflow agents Synap is not limited to a fixed list. It manages memory for customer support and sales agents, voice concierges, healthcare assistants, and multi-agent workflows alike. These are a few of the places teams run it today. [Healthcare](https://www.maximem.ai/use-cases/synap/healthcare)[Customer Support](https://www.maximem.ai/use-cases/synap/support)[Sales](https://www.maximem.ai/use-cases/synap/sales)[Voice AI](https://www.maximem.ai/use-cases/synap/voice-ai)[Multi-Agent](https://www.maximem.ai/use-cases/synap/multi-agent) [See all Synap use cases →](https://www.maximem.ai/use-cases/synap) 08/Security and trust ## Built for production and for enterprise Encrypted in transit and at rest Strict tenant isolation BYOK for model providers Self-hosted and air-gapped Our full security posture is published in one place: data flow, hosting, encryption, retention, deletion, subprocessors, tenant isolation, and DPA availability. [Read the security and privacy page →](https://www.maximem.ai/synap/security) Enterprise plans add VPC and private deployment, SSO and SAML, configurable RBAC, and custom SLAs. [See plans and enterprise options →](https://www.maximem.ai/synap/pricing) [Security and trust in the docs →](https://docs.maximem.ai/resources/security-trust) Get started ## Start building with Maximem Synap No credit card required. Google or GitHub sign-in. [Get Started Free →](https://synap.maximem.ai)[Read the docs](https://docs.maximem.ai) [View Synap pricing →](https://www.maximem.ai/synap/pricing)[Synap SDK reference →](https://docs.maximem.ai/sdk/initialization)[View open-source repo on GitHub →](https://github.com/maximem-ai/maximem_synap_sdk) ## Frequently Asked Questions ### What is Synap SDK? Synap is Maximem's agentic context management layer for AI agents. It gives your agents persistent, cross-session memory with automatic entity resolution, temporal awareness, and anticipatory retrieval. Synap integrates natively with 22 frameworks (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, and Smolagents) and scores 92% on the LongMemEval benchmark and 93.2% on LoCoMo. Free tier available with no credit card required. ### How do I integrate Synap into my AI application? Synap offers native SDK integrations for 22 agentic frameworks: 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, and Smolagents. Install the SDK, configure your API key, and start managing context with a few lines of code. Most developers are up and running in under 5 minutes. Visit docs.maximem.ai for the Quickstart guide, SDK reference, and framework-specific integration examples. ### What programming languages does Synap support? Synap provides Python and TypeScript/JavaScript SDKs, plus a REST API that works with any language. The SDK includes native wrappers for 22 agentic frameworks. Visit docs.maximem.ai for the latest SDK availability, language-specific guides, and API reference. ### How does memory persistence work in Synap? Synap manages memory through customized memory architectures built for each use case. It handles ingestion (deciding what to store), retrieval (surfacing the right context at the right time, including anticipatory pre-fetching at 15ms P50 latency), entity resolution (linking references like "my manager" and "Sarah" across sessions), temporal awareness (weighting recent context higher than stale context), and conscious forgetting (processing retractions and contradictions). All of this happens automatically without the agent needing to manage its own memory. ### Is Synap suitable for enterprise use? Yes. Synap is built with enterprise-grade security including encryption at rest, strict data isolation, and compliance-ready architecture. Enterprise plans include VPC/private deployment options, SSO/SAML, configurable RBAC, custom SLAs, and dedicated customer success management. Synap also supports BYOK (Bring Your Own Key) so you can use your own AI model provider credentials. Contact gaurav@maximem.ai for enterprise pricing and security documentation. ### How is Synap different from other memory solutions like Mem0 or Zep? Synap takes a fundamentally different architectural approach. Where Mem0 applies a universal memory model (extracted facts plus embeddings), Synap builds customized memory architectures per use case. Where Zep is built around a temporal knowledge graph (Graphiti), Synap focuses on anticipatory retrieval and latency optimization. On the LongMemEval benchmark, Synap scores 92% accuracy and 93.2% on LoCoMo, measured on an open-source harness anyone can reproduce. Synap also supports 22 agentic frameworks natively (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, and Smolagents) and delivers P50 retrieval latency of 15ms. Both Mem0 and Zep are solid tools. We encourage developers to evaluate all three against their specific use case. Read the full Synap vs Mem0 comparison at maximem.ai/compare/maximem-synap-vs-mem0 and Synap vs Zep at maximem.ai/compare/maximem-synap-vs-zep. ### How is Synap different from Supermemory? Supermemory is multimodal-first with connectors for documents, images, videos, and URLs. Synap is conversation-and-agent-first. If you need to process diverse content types into a searchable memory layer, Supermemory covers that well. If you need the highest verified accuracy (92% on LongMemEval, 93.2% on LoCoMo) at low latency for multi-turn AI agents (customer support, voice AI, workflow agents), that is Synap's focus. Synap's architecture is built around anticipatory retrieval (15ms P50), automatic entity resolution, temporal awareness, and conscious forgetting, which are capabilities specifically designed for agentic workloads rather than general-purpose document memory. Read the full Synap vs Supermemory comparison at maximem.ai/compare/maximem-synap-vs-supermemory. ### Is Synap open source? The SDK and the benchmark eval harnesses are open source, available on GitHub at https://github.com/maximem-ai/maximem\_synap\_sdk. You can self-host the full stack; we support it, it is just not out of the box. The managed cloud runs the engine, and adds the dashboard, analytics, and a free tier with no credit card required. ## From the blog [ ![How Synap Works Under the Hood](https://qirwvzn87kgnbyp6.public.blob.vercel-storage.com/assets/images/blogs/1779881264134-5uwjc816fih.webp) ### How Synap Works Under the Hood We launched Maximem Synap today. Here's a peek into how it is built. April 11, 2026 ](https://www.maximem.ai/blog/how-maximem-synap-works)[ ![Maximem Synap Updates: Higher Scores, 17 Integrations, and a Live Playground](https://qirwvzn87kgnbyp6.public.blob.vercel-storage.com/assets/images/blogs/1779946334625-v27hi5pm9w.webp) ### Maximem Synap Updates: Higher Scores, 17 Integrations, and a Live Playground Synap updates: 92% LongMemEval (up from 90.2%), 93.2% LOCOMO, 17 framework integrations, a browser playground, public pricing, and a free accuracy eval on your own agent. May 27, 2026 ](https://www.maximem.ai/blog/maximem-synap-updates-higher-benchmark-scores-and-more)[ ![Why We Built Synap](https://qirwvzn87kgnbyp6.public.blob.vercel-storage.com/assets/images/blogs/1779813829984-de1nx3rpc1q.webp) ### Why We Built Synap AI agents don’t fail from lack of memory, they fail because context doesn’t evolve. This article shows why current approaches break, introduces the Context Management Trilemma, and how Synap enables agents to learn, adapt, and stop forgetting over time. April 10, 2026 ](https://www.maximem.ai/blog/why-we-built-synap) --- Source: [https://www.maximem.ai/synap](https://www.maximem.ai/synap)