EverMemOS - An open-source AI long-term memory operating system developed by Chen Tianqiao's team.

What is EverMemOS?

EverMemOS, an open-source long-term memory operating system developed by the Shanda team led by Chen Tianqiao, provides AI assistants with persistent and searchable memory capabilities. Inspired by the human brain's memory mechanisms, it adopts a four-layer architecture, including an agent layer, a memory layer, an index layer, and an interface layer. The system integrates data from tools such as Slack, Gmail, and Notion, transforming fragmented information into unified and searchable memories. Its core innovation lies not only in being a memory "database" but also an "application processor," capable of proactively influencing the model's thinking and responses in real time. EverMemOS achieved a high score of 92.3% on the LoCoMo long-term memory benchmark, significantly surpassing existing performance. It supports both dynamic and static memory management, adapting to the diverse needs of teams and individuals.

Main functions of EverMemOS

• Memory retrieval and structuringExtract key information from conversations and transform it into structured memory cells and user profiles to help AI maintain context and recall past interactions during conversations.
• Multi-scene memory managementIt supports the collaborative management of dynamic and static memory, as well as personal and team memory, and provides optimal memory organization and application strategies for different scenarios.
• Active intelligence and reasoningIt possesses the ability to proactively identify problems, advance decision-making, and follow up on execution, and discover deep knowledge relationships by traversing complex information links through "multi-hop reasoning".
• Technical architecture designIt adopts a four-layer architecture (proxy layer, memory layer, index layer, and interface layer), integrates multiple technologies such as retrieval augmentation (RAG), vector retrieval, and knowledge graph, integrates mainstream large models, and intelligently selects the best AI capabilities.
• Memory portabilityUsers can export all data and knowledge at any time, including structured memories and insights, to avoid data being "hijacked".
• Supports multiple applicationsBy integrating with tools such as Slack, Gmail, and Notion, it supports team collaboration and personal knowledge management, improving team efficiency and individual productivity.

The technical principles of EverMemOS

• Inspired by the human brain's memory mechanismEverMemOS's design draws inspiration from the human brain's memory mechanisms, using a hierarchical architecture to store, retrieve, and apply memories, enabling the system to efficiently process and manage memory data.
• Four-layer architecture designThe system adopts a four-layer architecture: proxy layer, memory layer, index layer, and interface layer. The proxy layer is responsible for task understanding and allocation, the memory layer manages long-term memory, the index layer optimizes memory retrieval, and the interface layer enables integration with external applications.
• Multi-model integrationIt integrates multiple technologies such as Retrieval Augmentation (RAG), vector retrieval, keyword retrieval, and knowledge graph, and integrates mainstream large models such as Gemini, Claude, and ChatGPT, intelligently selecting the optimal AI capabilities according to different scenarios.
• Hierarchical memory retrievalExtracting continuous semantic blocks from dialogues, transforming them into contextual memory units, and then dynamically organizing them into structured memory solves the limitations of pure text similarity retrieval and improves the accuracy and efficiency of memory.
• Dynamic and static management of memoryIt supports collaborative management of dynamic memory (such as real-time dialogue) and static memory (such as documents and knowledge bases), and can provide optimal memory organization and application strategies according to different scenarios.
• The portability and security of memoriesUsers can export all data and knowledge at any time, including structured memories and insights, ensuring data portability and security and preventing data from being "hijacked".
• Active intelligence and reasoning abilityThe system has the ability to proactively identify problems, advance decision-making, and follow up on execution. It can traverse complex information links through "multi-hop reasoning" to discover deep knowledge relationships.

EverMemOS project address

• Project official websitehttps://evermind-ai.com/
• Github repository: https://github.com/EverMind-AI/EverMemOS/

Application scenarios of EverMemOS

• TeamworkIntegrate the tools used by the team (such as Slack, Gmail, Notion, etc.) to manage team knowledge in a unified manner, improve collaboration efficiency, and ensure information sharing and knowledge accumulation.
• Personal knowledge managementIt helps individuals transform fragmented information and deep thinking into a structured knowledge system, supports the transformation from ideas to detailed plans, and improves personal productivity.
• Enterprise applicationsIt provides enterprises with long-term memory management solutions, supporting persistent storage and intelligent retrieval of enterprise data, and assisting enterprises in knowledge management and decision support.
• EducationIt provides knowledge management and learning assistance for educators and students, helping them record the learning process, organize knowledge points, and improve learning efficiency.
• Intelligent Customer Service: Improve the response quality and efficiency of the customer service system through memory management, quickly retrieve historical conversation records, and provide more accurate customer service.
• Content creationIt supports creators in managing inspiration and creative materials, assists in content generation, and improves creative efficiency and quality.