The model is rented. The intelligence should be owned.

Engramic is where humans and agents author knowledge together — so every agent you deploy speaks your business, and the intelligence stays yours, not your model provider's.

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Make every agent fluent in your business.

Engramic is a knowledge graph your team authors: the decisions you've made, the goals you're working to, the constraints you operate under. It's delivered to every agent at the start of every task.

It's the knowledge layer the enterprise platforms are racing to build, without the complexity of large enterprise tools. No connector programme, no rollout, no consultancy. A team can be authoring on day one.

And it's authored, not observed. Your graph holds what your team decided and why, put there deliberately by people and agents working together. Shared with every agent at the start of every task. Over time, agents stop sounding generic and start sounding like your organisation.

AI
Assistant
via MCP
End of Q3 — 30 September.

Workflow · Create a goal

Here's what I'll record. Confirm to commit it to the workspace.

Create goal

Write a goal directly to your workspace

Increase customer retention by 50% by end of Q3

We've recruited a Forward Deployed Engineer to work on key customer accounts this FY; their contributions should help increase retention.

KR1

Ship customer-requested improvements from FDE account reviews

shipped per quarter → 3 1

KR2

Close FDE-raised product gaps within 30 days

median days to close → 30 62

Due 30 Sep 2026
Awaiting your confirmation…
Conversation snippetthread · pricing-strategy
1 recorded
Maya Patel14:31

Thinking about raising Tier B by 12% next quarter.

Alia14:31

That would conflict with the Q3 forecast the team committed to in May.

Maya Patel14:32

Right — forecast gets revised before any price change ships, then.

Alia14:32

That sounds like a constraint. Record it?

Recorded · constraint14:33

Tier B price changes wait on the Q3 forecast revision.

proposed by Alia · approved by Maya Patel · e_2026_0715

The knowledge that matters was never written down.

Anyone who has deployed an agent into a real organisation knows the moment: the agent did exactly what the documents said — and got it wrong. The branding changed for a project two days ago. The process doc it followed is the one everyone ignores. The customer nobody contacts mid-audit isn't flagged in any system.

That knowledge is what actually runs your organisation: the reasoning behind decisions, the exceptions, the constraints agreed in conversation. No retrieval system can reach it, because it was never captured anywhere. Your organisation runs on a language no model was trained on.

Engramic is where it gets written down. Authored by humans and agents together, as the work happens, before the thinking moves on.

Your agents have no yesterday.

The goal changed in Tuesday's stand-up. The doc still says otherwise. An agent working from your documents will act on January's truth in July — confidently.

No last quarter, no sense of what changed or why. The gap is continuity. A document tells an agent what the organisation knows. It doesn't tell it what the organisation has been through.

Engramic adds temporal continuity. What was decided, what changed, what superseded what — the arc of how things got here. Fluency isn't just knowing the facts; it's knowing which ones are current. When something new conflicts with what was agreed, it surfaces. That's organisational memory.

Topic timelinepricing-model
Active conflict
Decision Discovery Question Event
Today
  • 16:48Q3 forecast committed — 18% over planPlan Agent
  • 14:32Conflict surfaced — Tier B vs Q3 planAgent
  • 14:22Pricing tier A revisedGeorge Harrison
  • 11:05How will Tier B affect annual contracts?Paul McCartney
  • 09:42Initial pricing model committedFinance Team
  • 09:15Tier B raised — 12% uplift agreedJohn Lennon
6 events · 1 active conflict
Shared with every agentLive

graph · 214 items

  • ConstraintTier B price changes wait on the Q3 forecast revision
  • GoalIncrease customer retention by 50% by end of Q3
Shared with3 active
  • Claude Opus 4.8Active
  • GPT-5Active
  • Gemini 2.5 ProActive
  • Claude Sonnet 3.5Retired
Survived 1 model retirementKnowledge unchanged

Agent-Ready. Whatever the agent.

Agent-Ready is a property of the knowledge itself. A decision is not a constraint is not a goal; everything is anchored to a shared vocabulary, ordered in time, and shared with agents on demand. That's the difference between a graph and a well-written wiki. Both are authored, but only one can be handed to an agent at the start of a task, with no human assembling a prompt.

And because the form is open, it travels. The same knowledge reaches any agent — Claude today, another model tomorrow, several side by side — because the knowledge was never inside any of them. Your graph lives in Engramic and moves over MCP, the open standard for connecting agents to context. No proprietary runtime between your organisation and the model. Swap the model; the fluency stays.

Built for teams that never miss a beat.

One shared graph means shared visibility. When two decisions contradict each other, it surfaces for the team to settle while it's fresh, instead of six months later through an agent acting on stale truth. When a goal lacks a constraint, or a topic is half-specified, someone gets asked before an agent trips over it.

Alia is Engramic's librarian. They keep the collection coherent — spotting gaps, surfacing contradictions, asking the questions that turn what's in someone's head into something agents can use. They learn the language your team speaks, so every agent that connects can speak it too. Over MCP, any model can draw on the same checks.

Knowledge Health
last 30 days

12 open · 8 answered (24h) · 5 topics sharpened

Currently askingtopic · pricing-model

How does this interact with existing annual contracts?

Triggered by Tier B raised — 12% uplift. The graph has 23 active annual contracts on Tier B. Mid-term uplift may conflict with the renewal clause in the standard MSA.

Routed toRingo Starr · awaiting
Question activity
Engineering
4
Product
16
Commercial
8

Speaks MCP

Engramic plugs into any AI client that speaks the Model Context Protocol — no custom integration, no infrastructure project.

Works with

ClaudeCopilotMistralCustom MCP ClientsAnd more
Open standard · Linux FoundationMCP

Connect in minutes.

Engramic connects via MCP — no infrastructure deployment required to begin. Connect, and your agents start every task drawing on context your team has deliberately authored.

We're working with a small number of teams now. If you're building with agentic AI and ready to own your intelligence rather than rent it, get started.

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No commitment required. Connect via MCP and your team can be authoring in minutes.