Turn grid and asset data into governed operational decisions.
Turn inspection and network signals into maintenance situations, AI recommendations, human approvals, and controlled work orders — with a full evidence trail.
Grid & Asset Operations
Grid and asset decisions are assembled across GIS, inspection imagery, work orders, telemetry, and reports. Teams lose time reconciling evidence before they can prioritize maintenance or congestion actions.
Measure
Inspection throughput
Reduce
Planning lead time
Improve
Asset data completeness
Track
Exception resolution
Current workflow
- 01Collect fragmented evidence
- 02Reconcile asset identity
- 03Review exceptions manually
- 04Prepare decision note
- 05Approve and dispatch
Target workflow
- 1
Structure
Connect governed sources and resolve asset, inspection, and grid-segment objects.
- 2
Assess
Surface missing evidence, anomalies, and congestion or maintenance signals.
- 3
Recommend
Prepare a cited priority proposal with confidence and policy context.
- 4
Approve
Route consequential actions to the named operator or asset owner.
- 5
Prove
Export the sources, rationale, approvals, and outcome as an evidence pack.
Required data
- GIS and network models
- SCADA / ADMS signals
- Drone and LiDAR inspection
- ERP / EAM work orders
- Technical documents
Business objects
Human approval gates
- Maintenance priority change
- Operational intervention
- Work-order dispatch
- Regulatory report release
Governance profile
- NIS2-sensitive boundary
- Role and clearance-aware retrieval
- Human approval for operational actions
- Source lineage on every recommendation
AI co-workers
Inspection co-worker
Structures imagery and flags missing or inconsistent evidence.
Planning co-worker
Prepares ranked maintenance or congestion interventions with citations.
Evidence compiler
Builds the review trail for operations, risk, and regulators.
Evidence output
Grid & Asset Operations
- Source and model lineage
- Confidence and exception log
- Named approvals
- Decision rationale
- Deployment snapshot
Dedicated or private runtime with customer-controlled data boundaries and model policy.
Related use-case patterns
Grid Asset Inspection
Combine LiDAR digital twins with multi-modal AI inspection — visual, thermal, and corona/UV analysis — to build a living asset registry that guides maintenance priorities and field decisions for transmission and distribution operators.
View pattern PilotGrid Congestion Agent
Combine time-series models, weather feeds, and operator knowledge in a policy-gated agent that produces reviewable congestion forecasts — not black-box predictions.
View pattern ReferenceNIS2 Compliance Navigator
Link regulatory control frameworks to business capabilities and application portfolios — surfacing gaps, owners, and evidence requirements for audit-ready review.
View pattern