Scalable collective
intelligence
Engram reads your company's knowledge — Notion, Confluence, GitHub — and distills work patterns, conventions, and principles into context every AI tool consumes automatically.
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Sources
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Works with
The missing layer
Your AI stack has models and tools.
It's missing the context layer.
As AI handles more of the work, the people steering it need one place to define how your company operates — patterns, conventions, principles, rules — and have that context flow to every AI session automatically.
The problem
AI adoption without shared context is chaos
Every session starts from zero
AI knows nothing about your design system, brand voice, or API conventions. Engineers, marketers, designers — everyone wastes time repeating the same instructions in every chat.
Rule files don't scale
60,000+ repos have scattered CLAUDE.md files. Stale in two weeks, contradict each other across repos, and only help coders — leaving every other department without AI context.
Your knowledge base wasn't built for AI
Notion and Confluence are full of expertise — but AI can't navigate wikis or extract the actionable patterns buried in them. You need a layer that reads your existing knowledge and distills work patterns, conventions, and principles into context AI actually consumes.
Specialists can't scale
Your best designer reviews 5 PRs a day. AI makes 500 decisions that need that expertise. The bottleneck isn't knowledge creation — it's distribution.
End-to-end builders
Everyone becomes a builder
The old model: specialists in silos, waterfall handoffs, waiting for reviews. AI changes this — anyone can build end-to-end when their AI carries every specialist's expertise. No more bottlenecks. No more narrow lanes.
A developer
ships a full feature — UI, copy, security — without waiting for three other teams to review.
Because: Design system, brand voice, and security policies are already in every AI session.
A product manager
prototypes a working API integration without filing a ticket.
Because: API conventions, auth patterns, and error handling guidelines are built into the context.
A marketer
launches a campaign page that follows the design system and uses correct product terminology.
Because: Component usage, spacing rules, and product naming conventions are always available.
How it works
Three steps to shared context
Connect
Point at Notion, Confluence, GitHub, websites. Engram scans your existing knowledge — finds rules, identifies contradictions, spots gaps.
Structure
AI generates missing guidelines from your sources. Specialists review and approve. Quality scoring ensures consistency across domains.
Distribute
Engram compiles guidelines into the format each AI tool expects and keeps them in sync. Every session, every tool, every team — always up to date.
Smart routing
AI loads only what it needs
Engram compiles a lightweight routing hub (~200 tokens) for each AI tool. The AI reads the hub first, then loads only the relevant guidelines on demand.
CLAUDE.md — routing hub
# Engram Context Load docs as needed from .claude/docs/engram/ Available context:
~200 tokens — not thousands
Loaded guideline — full context on demand
Marketing team
.claude/docs/engram/brand-voice.md
Updated 2h ago# Brand Voice
Direct, confident, no jargon.
Second person ("you").
Contractions OK.
## Forbidden terms
Never say "leverage", "utilize",
"synergy", or "best-in-class".
## Tone by context
- Error messages: empathetic
- Marketing: bold, concise
- Docs: neutral, preciseGuideline health
Always accurate, never stale
Engram continuously monitors your guidelines — not just at setup, but every day. When something drifts, you know before your AI does.
Duplicates
Finds overlapping rules across domains and repos
Contradictions
Catches conflicting guidelines before AI does
Staleness
Flags guidelines when code or practices drift
Enterprise ready
Your context never leaves your infrastructure
Self-hosted
Rust-powered, ~20MB binary, <50MB RAM
Single Docker image on your own infrastructure. Sub-10ms context delivery. No data leaves your network.
BYO-LLM
Anthropic, OpenAI, Azure, Bedrock, Ollama
All AI processing uses your own models and API keys.
SAML SSO
Any SAML 2.0 identity provider
Enterprise authentication with your existing identity provider.
Audit trail
Immutable version history
Full change tracking on every guideline. Who changed what, when, and why.
FAQ
Common questions
Give every AI session your company's context
Set up in minutes. Start with one team, scale to the whole company.