Energy
Apply agentic AI across generation, grid, and field operations — predicting asset failures, forecasting load, and speeding regulatory and field workflows safely.
Energy and utility operators manage aging assets, volatile demand, and heavy regulatory obligations across sprawling infrastructure. We build AI systems that predict equipment failures, forecast load and generation, streamline field and outage operations, and give engineers instant access to technical knowledge. Deployments respect OT security and safety boundaries, turning your operational data into higher reliability and lower cost.
Problems we solve
The operational bottlenecks that hold enterprises back — and where AI delivers measurable impact.
Aging assets fail unpredictably
Transformers, turbines, and pipelines fail without warning, causing outages, safety risk, and emergency costs that dwarf planned maintenance.
Load and generation are hard to balance
Volatile demand and intermittent renewables make forecasting difficult, leading to costly imbalance, curtailment, and reliance on peaker plants.
Field and outage operations are inefficient
Dispatching crews, diagnosing faults, and restoring service rely on manual coordination, extending outages and driving up truck-roll costs.
Regulatory and reporting load is heavy
Compliance reporting, inspection documentation, and rate-case support consume specialist time and expose the utility to penalties for errors.
What we build
Production-grade capabilities, engineered for enterprise scale, security, and reliability.
Asset predictive maintenance
Models learn failure signatures from sensor, SCADA, and inspection data to flag at-risk transformers, turbines, and lines before they fail.
Load and generation forecasting
AI forecasts demand and renewable output at fine granularity, improving dispatch, trading, and grid-balancing decisions and cutting imbalance cost.
Field and outage operations agents
Agents help diagnose faults, prioritize and dispatch crews, and coordinate restoration, shortening outages and reducing unnecessary truck rolls.
Engineering knowledge assistant
A RAG assistant answers questions from equipment manuals, standards, and historical work, cutting the time engineers and technicians spend searching.
Compliance and reporting automation
AI drafts regulatory reports, inspection summaries, and rate-case support from operational data, with human review and a documented trail.
OT-safe, secure deployment
Systems run on-premise or at the edge within NERC CIP and OT security boundaries, advising operators without directly actuating control systems unless explicitly gated.
Why it matters
- Fewer unplanned asset failures and outages
- More accurate load and generation forecasts
- Shorter outages and lower truck-roll cost
- Faster engineer access to technical knowledge
- Compliance reporting drafted from live data
- Deployment that respects OT and NERC CIP
Implementation roadmap
Discovery & OT security scoping
We select a high-value asset class or workflow, assess sensor and SCADA data, and define OT-security, NERC CIP, and safety boundaries with your operations and security teams.
Pilot on one asset class
We connect to your historian and SCADA read paths, deploy predictive or forecasting models at the edge, and validate against real failures and demand history.
Production deployment
We integrate alerts into maintenance and dispatch workflows, harden edge deployment within OT constraints, and run under agreed reliability targets.
Scale across the network
We extend across asset classes and regions, standardize the data pipeline, and hand over monitoring so your engineering teams own and extend the models.
Common questions
Yes. We deploy on-premise or at the edge within your OT security zones, use read-oriented, non-intrusive integration, and align to NERC CIP and your internal security controls so critical infrastructure stays protected.
No, not by default. The AI advises operators and maintenance teams. Any closed-loop control is explicitly scoped, gated, and kept behind your existing safety and control systems only if you choose.
Yes. We integrate with SCADA, historians such as AVEVA/OSIsoft PI, GIS, and outage-management systems through their APIs and standard protocols, layering intelligence on top of your existing OT stack.
A meaningful history of sensor readings with some labeled failure events accelerates results. Where data is limited, we begin with anomaly detection and improve accuracy as more events are captured.
A single asset-class pilot typically demonstrates measurable failure or forecast improvement within a few months, giving a provable ROI before scaling across the network.