EverMemOS
EverMemOS is EverMind’s flagship long-term memory OS built as foundational infrastructure for next-generation AI agents. Unlike traditional memory databases that only retrieve past context, EverMemOS actively applies memory to an agent’s reasoning, decision-making, and responses—resulting in AI systems that feel consistent, personalized, and genuinely intelligent over time.
Designed with a brain-inspired, four-layer architecture, EverMemOS gives agents persistent “souls” by combining agentic reasoning, structured long-term memory, associative indexing, and seamless API/MCP integration. It supports everything from emotionally intelligent companion AI to complex, multi-agent enterprise collaboration.
EverMemOS has achieved state-of-the-art performance on major long-term memory benchmarks, including 92.4% on LoCoMo and 82% on LongMemEval-S, significantly outperforming prior approaches and setting a new industry standard for applied AI memory systems.
Most AI memory systems store context but fail to use it intelligently. EverMemOS changes that by treating memory as an active processor, not just storage. We picked EverMemOS because it solves one of the hardest problems in AI today: creating agents that actually remember, understand, and evolve over time—across both personal and enterprise use cases.
Four-Layer Brain-Inspired Architecture – Agentic, Memory, Index, and API/MCP layers modeled after human cognitive systems
Memory as a Processor – Applies memory directly to reasoning and generation, not just retrieval
Hierarchical Memory Extraction – Converts raw interactions into structured, continuous MemUnits
Dynamic Memory Graphs – Links related memories semantically beyond basic text similarity
Associative Retrieval Engine – Uses embeddings, key-value systems, and knowledge graphs for efficient recall
Extensible Modular Framework – Adapts memory strategies for different applications and scenarios
Multi-Agent Support – Enables coordinated memory across teams of AI agents
Enterprise-Ready APIs – Integrates cleanly with existing tools via API and MCP interfaces
Benchmark-Leading Performance – SOTA results on LoCoMo and LongMemEval-S
Production Integrations – First integrated with Tanka, an AI-native enterprise collaboration platform
Build Truly Persistent AI – Create agents that maintain long-term understanding of users and context
Deliver Coherent Experiences – Ensure AI behavior stays consistent across sessions and time
Enable Deep Personalization – Move beyond stateless interactions to evolving relationships
Support Complex Workflows – Power multi-agent enterprise collaboration with shared memory
Improve Decision Quality – Let past knowledge actively shape future outputs
Scale Across Use Cases – Use one memory system for both empathetic companion AI and professional tasks
Future-Proof AI Systems – Adopt memory infrastructure designed for next-generation agent architectures
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