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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.
Give AI tools a personal semantic memory layer for storing and recalling information.
Query and store private local memories with temporal reasoning and citations.
Give AI clients persistent memory with hybrid search and knowledge graph retrieval.
Provide AI assistants with persistent project memory to avoid repeating context.