Problem & risk
Operators face converged IT/OT threats, ageing infrastructure, and rising automation. AI that proposes switching actions, setpoints, or work orders needs the same discipline as safety interlocks: deterministic authorization before actuation, with evidence for regulators and internal audit.
Request a grid or OT workshop to map your control points.
Regulatory context
Expectations from NIS2, sector-specific resilience regimes, and AI governance guidance converge on demonstrable control of automated decisions affecting critical services.1
- Map to Ofgem resilience and reporting requirements, EU AI Act where applicable, and your national cyber/OT security frameworks.
Solution
TrigGuard is the gate between inference and action: policy evaluates each proposed operation; DENY and SILENCE prevent harmful execution; PERMIT proceeds with signed receipts for post-incident review and compliance packs.
- Sub-second evaluation for operational loops
- Clear audit trail for safety and compliance cases
- Policies aligned to site-specific risk appetite
Integration points
Integration points include EMS/SCADA-adjacent orchestration layers, DER aggregation platforms, outage management, work order systems, and predictive maintenance pipelines before tickets become field actions.
Next steps
Choose how you want to engage—each action logs intent for follow-up when analytics is enabled.
Related reading & programme notes
- Why AI in grid operations needs a safety interlock
- Navigating the EU AI Act for energy operators
- From predictive maintenance to autonomous switching: governance
Long-form articles on the content calendar can deep-link here as they ship.