Engram FAQs

Question 1

What is Engram?

Accepted Answer

Engram provides AI coding agents with persistent, searchable cross-session memory. It uses a unique 'metabolic lifecycle' to ensure knowledge stays relevant and up-to-date, expiring unused information while promoting frequently accessed insights.

Question 2

How does Engram manage knowledge with a 'metabolic lifecycle'?

Accepted Answer

Knowledge nodes in Engram are born with a Time-To-Live (TTL). Recalling a node keeps it alive and can promote it to permanent status, while neglect allows it to expire. This ensures only valuable and actively used information persists.

Question 3

Is Engram private and cost-effective?

Accepted Answer

Yes, Engram operates fully locally. It requires no external APIs or LLM token costs, guaranteeing complete data privacy and cost-efficiency. Your agent's memory stays entirely within your control.

Question 4

Can I customize the embedding models used by Engram?

Accepted Answer

Absolutely. While Engram ships with MiniLM-L6 as the default local embedding model, it is fully swappable. You can easily integrate other models like OpenAI, Cohere, or your own custom embedding solutions.

Question 5

What AI agent platforms can use Engram?

Accepted Answer

Engram is designed to integrate seamlessly with Claude Code, Cursor, and any other MCP-compatible AI client. It provides a core set of memory management tools for versatile usage across different agent environments.

Engram

Engram

Key Features

Use Cases

Key Features

Use Cases