The Memory Layer for AI Agents - Drop-in memory infrastructure for AI agents and apps. Context that persists. Built for production.
Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems. Built for enterprise, Memori works with the data infrastructure you already run, no rip-and-replace, and deploys across managed cloud, single-tenant cloud, VPC, and on-premises.
Memray is a memory profiler for Python
Personal memory across agents
One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.
Agent S: an open agentic framework that uses computers like a human
Cross-platform lib for process and system monitoring in Python
https://arxiv.org/abs/2606.28344. The end of web parsing. The beginning of scalable pixel-native search. link: https://pixelrag.ai/
An advanced memory forensics framework
Memory library for building stateful agents
MineContext is your proactive context-aware AI partner（Context-Engineering+ChatGPT Pulse）
Volatility 3.0 development
MS-Agent: a lightweight framework to empower agentic execution of complex tasks
[ICML'26] SimpleMem: Efficient Lifelong Memory for LLM Agents — Text & Multimodal
ReMe: Memory Management Kit for Agents - Remember Me, Refine Me.
Framework for AI agents to build and maintain a digital brain through Obsidian wiki | Memory System for Agents
🚀 EvoAgentX: Building a Self-Evolving Ecosystem of AI Agents
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