AI company memory that carries context across work
AI company memory gives agents access to the relevant history behind a task: decisions, customers, promises, pricing, policies and communication patterns.
What is company memory for AI?
Company memory is an organized layer of institutional knowledge that AI can retrieve during work. It includes explicit facts from documents and the relationships that make those facts meaningful: who approved a decision, which customer received an exception, what changed and which source is current.
Memory is not the same as sending an entire archive to a model. Useful systems select context for the task, preserve source links and apply permissions.
What should it remember?
- Customer history, commitments and unresolved questions.
- Offers, pricing boundaries and approval requirements.
- Product details, policies and known edge cases.
- Decisions, their reasoning and the evidence behind them.
- Examples of company voice and preferred working patterns.
How businesses use AI memory
An email agent can retrieve the customer's prior conversation before drafting. A support agent can combine the current policy with a previous promise. A founder agent can assemble a briefing from recent decisions and unresolved risks. The shared memory creates continuity across these jobs.
Memory needs controls
More memory is not automatically better. Sources need explicit permissions, stale information needs handling, contradictions should be visible and sensitive actions need approval. Permanera is designed around connected sources, reviewable assumptions, deletable data and draft-first work.