Last updated 06-27-2026
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EverMind
EverMind builds memory infrastructure for LLM agents that need to remember across sessions, platforms, and time. Its flagship product, EverOS, turns fragmented chat logs and documents into structured, self-evolving memory so agents stay consistent instead of resetting every conversation. The company also offers EverMe, a personal memory hub that lets multiple agents share one profile of you.
Most agent stacks treat memory as a vector store: embed text, retrieve chunks, paste into the prompt. EverOS takes a different path with an engram-inspired lifecycle that structures interactions into MemCells and MemScenes, then reconstructs only the context needed for each query. The team reports state-of-the-art scores on long-term memory benchmarks like LoCoMo (93.05%), LongMemEval (83%), and HaluMem (93.04%).
EverOS ships as a managed cloud service or self-hosted stack under Apache 2.0. One API call ingests messages, images, PDFs, spreadsheets, and URLs. Agents can record task trajectories as Cases that distill into reusable Skills over time. Integrations include MCP servers and plugins for Claude Code, OpenClaw, and related coding agents.
The platform targets teams building multi-agent systems, personalized companions, customer support bots, and company knowledge bases. Use cases on the site range from AI wearables and coding agent orchestration to a public reunification project called Reunite.
Agent trajectories become Cases that self-promote into reusable Skills
One API ingests PDFs, images, docs, spreadsheets, and URLs together
Memory Bank UI separates user, group, and agent memory layers
93%+ LoCoMo accuracy with under 500ms p95 retrieval latency
Cloud-managed or self-hosted with Markdown export and Apache 2.0 license
MCP server plus Claude Code and OpenClaw plugin support
Open-source EverOS stack ships under Apache 2.0 with Markdown export and no vendor lock-in.
Reports 93.05% accuracy on LoCoMo with under 500ms p95 retrieval latency.
One API ingests messages, images, PDFs, spreadsheets, and URLs without separate pipelines.
Agent trajectories distill into reusable Skills that evolve across your agent team.
Supports SQLite, Postgres, FAISS, Milvus, and pgvector for self-hosted deployments.
Cloud Pro is free during beta, with $25/mo pricing listed for after launch.
Enterprise tier requires contacting sales for custom limits.
Memory perception and consolidation add configurable LLM call overhead.
What is EverOS?
EverOS is EverMind's self-organizing memory operating system for LLM agents. It structures long interaction histories into MemCells and MemScenes so agents can stay consistent, updatable, and traceable over time instead of relying on flat vector retrieval.
How is EverOS different from classic RAG?
Classic RAG stores text, embeds it, retrieves chunks, and pastes them into the prompt. EverOS runs a full memory lifecycle: it structures raw interactions, consolidates them into semantic themes, and reconstructs the minimal context needed for each query.
Does EverMind have a free plan?
Yes. EverOS Cloud offers a free tier with 3 Memory Spaces, 50,000 MCU per month, and 100,000 Retrieval API Calls per month. The open-source Community edition can also be self-hosted at no cost under Apache 2.0.
Can I self-host EverOS?
Yes. EverMind publishes the full EverOS memory stack as open source under Apache 2.0. You can run it on your own infrastructure with the same API as the cloud service and export memories as Markdown at any time.
What storage backends does EverOS support?
EverOS supports SQLite, Postgres, and vector databases with embeddings such as FAISS, Milvus, and pgvector. Memories are stored as transparent JSON objects you can inspect directly.
Does EverOS work with local LLMs?
Yes. EverOS can plug into any model, including OpenAI, Qwen, Llama, and local models exposed through an API wrapper. You can also use lightweight models for memory extraction and heavier ones for consolidation.
Is EverOS compatible with LangGraph or Haystack?
Yes. EverOS can serve as a plug-in memory backend for agent frameworks like LangGraph and Haystack, and it also ships MCP server support for Claude Code, OpenClaw, and similar coding agents.