Engram

Founded by Dan Biderman in 2024

Train AI models on your company's internal data and context

Cost

Demo

Rating

★ People love it

Time to value

Requires Expertise

You can use Engram to train AI models on your organization's specific data — from GitHub, Slack, Notion, and other internal sources — so the models actually retain and understand your context instead of re-reading documents every session. Engram's API lets you build agents that learn from large shared knowledge workspaces, draw connections across company knowledge, find precedents across documents, and stay up-to-date as your data changes. It uses 1%-10% of the tokens compared to standard context-window approaches.

What Engram does

Train AI models on internal company documents and communication dataBuild API-connected agents that retain knowledge across conversationsConnect data sources like Slack, Notion, and GitHub to a custom modelRun continuous retraining cycles to keep models updated with new informationQuery an AI agent for cross-document connections and forgotten detailsReduce token usage by replacing context-window retrieval with trained model knowledgeDeploy customized AI agents inside enterprise tools like Microsoft 365Search and retrieve precedents across large knowledge repositoriesTrains AI models directly on your company's internal data rather than relying on context windowsModels retain knowledge across sessions — they don't forget when you close the chatUses 1%-10% of the tokens compared to standard retrieval approachesContinuously retrains on updated company data (daily, moving toward hourly and per-minute)Draws unexpected connections across documents and finds errors humans missedProvides an API for building agents that learn on large shared knowledge workspacesIntegrates with Notion, Slack, GitHub, and Microsoft 365 as data sourcesScales across large enterprise knowledge bases used by firms like Harvey and Microsoft