Trusted AI Execution for Operational Systems – Industrial Collaboration and R&D Partners

Qognetix is a UK deep-tech company developing Trusted Execution (TE), a computational approach designed to bridge the gap between AI-generated decisions and their safe, controlled and accountable execution in real-world operational systems.

While advances in AI have significantly improved prediction, optimisation and decision-making, deploying these capabilities into operational environments introduces additional challenges around execution governance, reliability, traceability, intervention and human oversight.

Our Trusted Execution technology addresses these challenges by providing a foundation for governing intelligent behaviour at runtime, enforcing operational constraints and supporting bounded autonomy.

We are seeking organisations interested in exploring how these capabilities could strengthen the deployment of AI within industrial, infrastructure and autonomous systems.

What We Offer

Qognetix is developing a sovereign, hardware-agnostic computational stack incorporating Trusted Execution (TE), Persistent Intelligence (PI), our proprietary SIBINE execution environment and supporting development tools.

Our technology is designed to support:

• Runtime Governance: Controlling how AI-generated decisions are translated into operational actions within defined constraints.

• Bounded Autonomy: Establishing operational boundaries for autonomous systems, including escalation and intervention mechanisms.

• Execution Traceability: Supporting inspection, reconstruction and accountability of intelligent system behaviour.

• Persistent Execution State: Maintaining operational context across successive decisions and actions.

• Human Oversight: Supporting operator intervention and governance of autonomous processes.

• Hardware Independence: Enabling deployment across diverse computing architectures, including resource-constrained environments.

TE is intended to complement existing AI models, optimisation platforms and automation systems rather than necessarily replace them.

Partners Sought

We are particularly interested in connecting with:

• Industrial AI Developers: Organisations developing AI-driven optimisation, forecasting, automation or autonomous decision-making solutions.

• Industrial Operators: Energy networks, utilities, manufacturers and infrastructure operators exploring operational AI deployment.

• Systems Integrators: Companies integrating AI capabilities into existing industrial control and operational technology environments.

• Research Organisations: Universities, Catapults and research institutes working in trustworthy AI, runtime assurance, autonomous systems and cyber-physical systems.

• Technology Providers: Developers of robotics, digital twins, distributed energy management, industrial IoT and intelligent infrastructure platforms.

Potential Collaboration Areas

We are interested in exploring projects involving:

• Governed execution of AI-generated operational decisions.

• Integration of runtime assurance mechanisms with existing AI platforms.

• Safe deployment of AI-based optimisation and autonomous control.

• Execution traceability, operational auditability and intervention.

• AI deployment in resource-constrained or connectivity-limited environments.

• Evaluation of trusted execution architectures using industrial simulations, digital twins or operational testbeds.

Expected Collaboration Outcomes

Our objective is to establish collaborative projects that progress from technical feasibility through independent validation and industrial demonstration.

Potential outcomes include joint feasibility studies, proof-of-concept integrations, comparative benchmarking, industrial demonstrators, pilot deployments and collaborative funding applications.

We welcome discussions with organisations forming consortia for BridgeAI, Innovate UK and other UKRI-supported innovation programmes.

Our aim is to help organisations move beyond AI that predicts or recommends towards intelligent systems whose actions can be governed, inspected and controlled throughout execution.