Memory is becoming a first-class AI problem.
Intuilective explores the architecture, safety and governance of persistent AI memory. Our research focuses on questions including:
- How should an AI system determine what deserves to become memory?
- How should memories strengthen, weaken or decay?
- How can memory provenance be preserved, and learning remain auditable?
- How does persistent memory change AI safety?
- How do organisations prevent accumulated memory from introducing bias, contamination or drift?
- How can humans inspect and govern what an AI system has learned?
ARCHÉ
Research from first principles.
ARCHÉ is Intuilective's research initiative exploring the foundations of memory, learning and intelligence. Our work examines memory not simply as additional context for a model, but as a constituent part of intelligent systems.
Constitutive memory
How persistent memory changes the nature and behaviour of an intelligent system.
Longitudinal AI safety
What happens to alignment and behaviour when AI systems accumulate experience over time.
Verifiable learning
How systems can learn from outcomes without allowing unverified experience to silently become future behaviour.
Memory governance
How persistent machine memory should be controlled, inspected, corrected and audited.
The next frontier of enterprise AI is not larger context. It is institutional continuity.