AI BriefingSupermemory - Memory & Context Engine for AI
Key point
A memory layer engine that provides fact extraction, automatic forgetting, and hybrid search to supplement AI's short-term memory limitations.
Details
This is a memory and context layer for AI that automatically extracts facts from conversations to build user profiles, and features automatic forgetting that handles contradicting information and deletes expired information.
Through Hybrid Search combining Memory and RAG, it delivers both knowledge base documents and personalized context in a single query, maintaining user profiles at a fast speed of approximately 50ms. It supports connectors that sync in real-time via webhook with various services such as Google Drive, Notion, and GitHub.
Developers can implement memory, RAG, and profile features through a single API without needing to set up a separate Vector DB or build an embedding pipeline. It also integrates with major AI coding tools such as Claude Code, Cursor, and VS Code through an MCP (Model Context Protocol) server.
By integrating with Ollama, it operates in a fully offline environment, and it ranked 1st on 3 major AI memory benchmarks including LongMemEval. This project is provided under the MIT License.
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