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Give AI agents persistent memory with natural language recall and perspective fan-out.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Engram" yet — see the docs or source repo.
Store the following project background, key decisions, and action items in Engram memory, and create a searchable summary for future Q&A: Project Alpha aims to launch an enterprise knowledge base assistant in 8 weeks; Slack integration has been prioritized; the current risk is messy document permissions; next week's tasks are completing the permission mapping plan and pilot customer interviews.
Persisted project context with a structured memory summary for later natural-language recall.
Query Engram: Why did we prioritize Slack integration earlier? Summarize it from product, technical, and customer perspectives, including related decisions, risks, and action items.
Relevant past memories organized into a clear multi-perspective summary.
Use Engram to create a shared memory space for a research agent, writing agent, and review agent: save this week's user interview findings, competitor observations, and content draft requirements; then return the most relevant memory cues for each agent.
A shared persistent memory with tailored context cues distributed to different agents.
Give AI agents shared long-term memory with git-backed markdown knowledge storage.
Provide a local memory layer for coding agents to capture and recall facts.
Store, search, and manage personal memories locally with hybrid semantic recall.
Give AI tools a personal semantic memory layer for storing and recalling information.
Provide Git-backed Markdown memory and clean search for AI agents.
Query and store private local memories with temporal reasoning and citations.