Company Brain and context
What is Enterprise Context Management? Definition and examples
Also: ECM, context management, shared context, context layer
In short
Enterprise Context Management (ECM) keeps a company's context current, reviewed and usable for people and AI agents. That context covers goals, decisions, knowledge and rules. ECM decides which state applies, who approves it and how changes flow back into the source systems.
Why it matters: AI agents only scale once all of them work from the same valid context.
- 01
Decide
Leadership sets what applies
- 02
Connect
Sources and AI agents read along
- 03
Review
Contradictions surface
- 04
Approve
Changes flow back
Why does Enterprise Context Management matter for your company?
Most AI errors in companies are not model errors but context errors: the agent does not know the current decision, reads an outdated document or gets contradicting instructions. More compute does not fix that.
ECM turns context into shared infrastructure, like finance or data. Leadership decides what applies. Owners approve changes. Every team and every AI agent reads from it. The principle stays simple: one state, with its reasoning.
Enterprise Context Management in detail
Context Layer
A context layer is the layer between a company's source systems and its AI models that provides the context that currently applies. It controls what an AI agent sees, which state applies and who may change it, independent of the model.
Today every team builds its own connections: one assistant reads SharePoint, another Jira, a third a copy of the price list. Each connection has its own permissions and its own state. When you switch model or tool, the work starts again.
Example: Three teams, three AI assistants, three truths
Sales, support and engineering have each built their own assistant, with their own prompts and sources. After a price change the support assistant answers with the old price list, the sales assistant with the new one, and the coding agent still builds the old discount model.
With Enterprise Context Management there is one approved state of the price list. All three assistants read it, deviations in documents and tickets become visible, and the correction goes to the owners.
3 common mistakes to avoid
Context per prompt instead of per company
Every team writes its own system prompts. That creates many small truths nobody maintains.
Indexing everything, reviewing nothing
A search across all sources also finds what is outdated. Context needs owners who say what applies.
Treating it as an IT project
Which strategy, prices and commitments apply is for leadership to decide, not IT.
Step by step
- 1
Name the critical context
Strategy, priorities, prices, customer commitments: what must never be outdated?
- 2
Assign owners
One person per topic who approves changes.
- 3
One state for everyone
People and AI agents read from the same source, for example through MCP.
- 4
Check deviations continuously
Where documents, tickets or code contradict, a proposal for approval is created.
Bring one important decision.
In 30 minutes with Marc or Simon we show where your work drifts from the decision today.
Meet the Company BrainRead on in the PM Lab
Articles that go deeper.
Related terms
- Company Brain →A Company Brain is a company's shared memory: it connects knowledge, decisions and meeting notes from the tools you already use in one place.
- Context Engineering →Context engineering is the work of giving an AI model exactly the right context for a task: the goal, the rules that apply and the knowledge it needs.
- AI governance →AI governance is the set of rules a company uses to decide who may use AI for what, with which data and under whose responsibility.