Universal memory layer for AI Agents
OpenViking is an open-source context database designed specifically for AI Agents(such as openclaw). OpenViking unifies the management of context (memory, resources, and skills) that Agents need through a file system paradigm, enabling hierarchical context delivery and self-evolving.
Memory engine and app that is extremely fast, scalable. The Memory API for the AI era.
What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?
Memray is a memory profiler for Python
Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.
Memory for 24/7 proactive agents like openclaw (moltbot, clawdbot).
Memori is agent-native memory infrastructure. A SQL-native, LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems.
Agent S: an open agentic framework that uses computers like a human
Lightweight real-time memory management application to monitor and clean system memory on your computer.
Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.
Hindsight: Agent Memory That Learns
Your favorite self-hostable alternative to Google Timeline (Google Location History)
AI memory OS for LLM and Agent systems(moltbot,clawdbot,openclaw), enabling persistent Skill memory for cross-task skill reuse and evolution.
Turn any code, or knowledge base (Karpathy LLM wiki), into an interactive knowledge graph you can explore, search, and ask questions about. Graphs that teach > graphs that impress. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
An advanced memory forensics framework
MineContext is your proactive context-aware AI partner（Context-Engineering+ChatGPT Pulse）
Deliver experiences best suited to a user's device and network constraints
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