Engram: Solving Memory for AI Systems

AI systems today are powerful, but they still struggle with long-term memory. Every interaction often starts from scratch, forcing models to relearn context in the moment.

Engram is building a new approach. Its product studies an organization’s world ahead of time and compresses what it learns into a compact, reusable memory. The name comes from neuroscience: an engram is the trace a memory leaves in the brain.

The result is models that can match or outperform frontier systems while using as little as 1 to 10% of the tokens, and that improve the more they are used. As an organization uses Engram, its memory becomes more proprietary, more useful, and more deeply tied to how that organization works.

In this conversation, we discuss Engram’s founding insight, the technical foundations behind machine memory, and why the team is uniquely suited to tackle one of the most important challenges in AI: giving systems durable, dynamic, personalized memory.