Pre-execution control for AI in regulated workflows

ExecLayer is developing execution-control infrastructure for AI systems operating in regulated and high-consequence environments.

As organisations move from AI systems that analyse information and generate recommendations to agents that update records, initiate workflows, invoke tools and take actions across enterprise systems, the control problem changes. Monitoring and audit trails can show what happened, but they do not necessarily determine whether a particular action was authorised before it occurred.

ExecLayer is designed to provide a deterministic control point between AI-generated intent and execution. It evaluates a proposed action against explicit constraints concerning actor identity, delegated authority, permitted scope, target resources, purpose, applicable policy and contextual risk.

Based on those constraints, the system can allow, deny or escalate the proposed action before execution. It can also generate an evidence record documenting the request, applicable controls and resulting authorization decision.

Potential pharmaceutical applications include:

- AI-assisted deviation and CAPA workflows

- Controlled changes to GxP records

- Quality-management system actions

- Regulatory operations and document workflows

- Supplier-quality decisions

- Manufacturing and engineering workflows

- AI agents operating across multiple validated systems

ExecLayer is intended to complement existing identity management, cybersecurity, validation, quality-management, monitoring and audit controls. It is not a substitute for GxP validation, accountable human oversight or regulatory review.