Memory that helps, not memory that drifts
Agents need short-term context, durable facts and a way to forget. We design memory layers and knowledge graphs that keep agents consistent across sessions.
How we approach it
Long conversations overflow context windows and quietly lose detail. We separate working memory for the current task, episodic memory of past sessions and a structured store of durable facts, each with its own rules for writing, reading and expiry.
A knowledge graph gives agents a map: entities and relationships they can traverse, rather than rediscovering the same connections in every prompt.
Remembering is a privacy decision
We design what is stored, for how long and who can see it, before building the mechanism.
- Memory writes are explicit and reviewable.
- Users can inspect and correct what is remembered.
- Isolation between tenants and between users.
Step by step
Working memory
Task state for the current run.
Episodic memory
Summaries of past sessions.
Durable facts
Entities and relationships in a graph or tables.
Curate
Rules for what is stored, updated and forgotten.
What you receive
Layered memory
Different stores for different lifetimes.
Entity graph
Relationships the agent can traverse.
Privacy controls
Per-user and per-tenant boundaries.
Memory hygiene
Deduplication, correction and expiry.
Common questions
Is memory just a bigger context window?
No. Large contexts are expensive and noisy. Structured memory retrieves what matters for the task.
Can users delete what the agent remembers?
Yes. Deletion and correction are part of the design.
When is a graph worth it?
When relationships between entities drive the questions, such as dependencies, ownership or hierarchies.
Scope your agent system with an engineer
Bring the process you want to automate. We will talk through the architecture, the risks and a realistic first release.