A developer released maximem, a memory layer that keeps AI context across messages, sessions, and apps, as free and open-source. The core is free with an open-source SDK rather than paid tiers, motivated by widespread complaints about GPT and Claude forgetting context.
A developer SDK that gives AI agents persistent memory so they retain information between sessions. The team built it after finding existing agents forgot everything between sessions. Aimed at developers building agentic applications.
A developer SDK that gives AI agents persistent memory so they retain information between sessions. The team built it after finding existing agents forgot everything between sessions. Aimed at developers building agentic applications.
Maximem Synap is a memory SDK that gives AI agents persistent memory across sessions. It uses LLM-based typed extraction and entity resolution to store user preferences and context so agents stop re-asking known information. It targets developers building agents who lose context between sessions.
Maximem Synap is a memory SDK that gives AI agents persistent memory across sessions. It uses LLM-based typed extraction and entity resolution to store user preferences and context so agents stop re-asking known information. It targets developers building agents who lose context between sessions.
Clippy Vision is a local, open-source tool that passively watches your screen to remember your context, so you can ask it questions instead of re-explaining your work to AI chatbots. It solves the problem of lost context in AI conversations for users who multitask or do long research sessions.
Clippy Vision is a local, open-source tool that passively watches your screen to remember your context, so you can ask it questions instead of re-explaining your work to AI chatbots. It solves the problem of lost context in AI conversations for users who multitask or do long research sessions.
A self-hosted memory layer for AI agents where plain markdown files are the permanent source of truth, topped by a local retrieval index combining vector embeddings, full-text search, and a graph of related memories. Agents connect to recall past decisions across sessions without data living on third-party servers. It solves context loss between sessions for people running personal AI agents.
A self-hosted memory layer for AI agents where plain markdown files are the permanent source of truth, topped by a local retrieval index combining vector embeddings, full-text search, and a graph of related memories. Agents connect to recall past decisions across sessions without data living on third-party servers. It solves context loss between sessions for people running personal AI agents.
Ormah shares long-term memory across AI coding agents like Claude Code, Codex and Pi, injecting relevant context before each agent response. It stores memory locally as readable Markdown, links related memories, merges duplicates, and expires stale ones. It solves re-explaining preferences and decisions to each new agent, for developers using multiple AI agents.
Ormah shares long-term memory across AI coding agents like Claude Code, Codex and Pi, injecting relevant context before each agent response. It stores memory locally as readable Markdown, links related memories, merges duplicates, and expires stale ones. It solves re-explaining preferences and decisions to each new agent, for developers using multiple AI agents.