Overview

Engram Lab builds a learned memory layer for enterprise AI. It separates an AI system’s reasoning and inference from its memory, allowing the model to study a client’s data—documents, workflows, and institutional knowledge—in advance and store it in a compact, reusable memory. This memory layer is continuously improved and used to supply context, dramatically reducing token usage (by about 90–99%) and AI-related costs (by roughly 10–100x). The company targets large enterprises with customized models that autonomously adapt to each customer’s needs, and it tests deployments through partnerships with firms like Microsoft, Notion, and Harvey, including integration with Microsoft 365 and Azure GPU capacity. Engram’s goal is to make enterprise AI more efficient and affordable by enabling context-aware reasoning that relies on a client-specific memory rather than reprocessing the entire context for every query.

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