Agentic systems
Governance and human approval gates for autonomous AI agents.
The problem
Autonomous agents that take actions without human approval create regulatory and reputational risk. The EU AI Act explicitly requires human oversight for high-risk systems. But naive "human in the loop" patterns break the workflow and add latency that defeats the purpose of automation.
What we build
We design approval gates that distinguish routine actions (which proceed automatically) from novel or high-risk actions (which require human sign-off). The system learns from approvals and refusals, tightening or loosening gates based on observed outcomes.
The approval interface shows the agent's reasoning, the action it wants to take, and the evidence it relies on. The human approver sees enough context to make an informed decision in under 30 seconds.
Evidence of control
We document:
- Which actions require approval and which do not
- How the system escalates when confidence is low
- Audit trail of every approval and refusal
- Performance: approval rate, false-positive rate, mean time to approval
What this solves
Agentic systems can proceed at scale while maintaining human control where it matters. We have deployed this pattern in customer service (agent drafts responses, human approves before send) and financial operations (agent proposes transactions, compliance approves).
Engagement model
Fixed-scope design, prototype, and production implementation. Timeline: 6–10 weeks. Deliverables include working approval system, integration guide, and compliance documentation suitable for regulatory review.
Related services: Sovereign cloud integration · AI assurance