Conversational AI & Memory
State and memory architecture for assistants that need to remember correctly, forget appropriately, and stay consistent over time.
Sounds familiar?
- 01The assistant forgets what it was told two conversations ago.
- 02Contradictions accumulate as conversations get longer.
- 03Session hand-offs lose context users expect to persist.
- 04Memory grows unboundedly, dragging cost and latency with it.
What it costs to leave it
- Users repeat themselves and disengage.
- Long-running use cases (coaching, ops, support) behave unreliably.
- Memory bugs surface as credibility problems, not just technical ones.
What the engagement covers.
Memory architecture: working memory, episodic memory, durable user facts.
Temporal context: what changed, when, and what supersedes what.
State handling across sessions, devices and channels.
Memory evaluation: consistency, contradiction and recall testing.
Privacy-aware retention: what to keep, what to decay, what to purge.
How the engagement runs.
Define what the product must remember, and for how long.
Memory tiers, write/read policies, and conflict resolution.
Consistency and recall suites across realistic timelines.
Instrumented rollout with retention and purge behavior.
Deliverables
Memory architecture specification
State and session persistence design
Memory evaluation suite (consistency, recall, contradictions)
Retention and decay policy with privacy review notes
Instrumentation for memory behavior in production
A good fit when
- Products with ongoing relationships between users and assistants.
- Support/copilot products where continuity is the value proposition.
- Teams whose memory behavior has become a scaling bottleneck.
Probably not, when
- Single-turn Q&A features with no continuity requirement.
- Teams expecting “memory” to be a one-line library call.
Common questions.
Is this just long context?
No. Long context helps but does not resolve contradictions, does not decay stale facts, and gets expensive. Memory architecture is about what to store, surface and forget.
Can memory be evaluated?
Yes. Recall, consistency over time, contradiction handling and decay behavior are all testable properties with realistic conversation timelines.
How do you handle privacy?
Retention is designed deliberately: what is stored, for how long, what is purged on request. Engineering practices are described accurately rather than claimed certifications.
Can you integrate with our existing identity and data systems?
Yes. Memory state should live where your other user data lives, governed by the same controls.