Runtime AI Assurance: Beyond Monitoring and Explainability

Qognetix is seeking research, technology and industrial partners to advance runtime assurance for autonomous and adaptive intelligent systems.

Traditional AI assurance frequently focuses on model evaluation, explainability, documentation and compliance. However, systems that act autonomously, maintain persistent state or adapt through experience introduce additional operational assurance challenges.

Our research explores how assurance can extend into system execution through:

- Continuous monitoring of operational behaviour

- Verification of execution boundaries and constraints

- Intervention and governance escalation mechanisms

- Causal traceability and execution reconstruction

- Evidence generation for independent technical assessment

- Assurance of persistent and adaptive intelligent systems

We are particularly interested in collaboration with organisations developing AI assurance frameworks, measurement methodologies, testing environments and technical standards.

Potential cooperation includes joint research, experimental evaluation, independent benchmarking, demonstrator development and collaborative funding proposals.

The objective is to investigate practical mechanisms for generating verifiable evidence of intelligent system behaviour throughout operation.

We welcome discussions with national laboratories, universities, assurance organisations, industrial technology providers and operators of safety- or mission-critical systems.