The energy and utility industry is rapidly evolving, and artificial intelligence (AI) is no longer a futuristic concept — it’s a practical tool ready to drive operational improvements today. Whether optimizing grid performance, predicting equipment failures, automating compliance processes, or strengthening OT cybersecurity, AI is delivering measurable value right now. 

However, many utilities are stuck in endless exploration and pilot projects, slowing their progress and missing near-term opportunities. The key to unlocking AI’s full potential lies in combining rapid prototyping with functional expertise, enabling utilities to focus on the most impactful use cases while learning how to scale AI across their organizations. 

• Deep industry knowledge across electric and natural gas utilities 

• Experience translating AI potential into practical, working solutions 

• A structured approach that accelerates AI adoption while mitigating risks 

We help utilities rapidly prototype use cases, learn through experimentation, and prepare governance and data processes to support long-term success. 

AI success doesn’t require perfect data or fully mature governance frameworks. Our approach to rapid prototyping allows utilities to quickly test AI tools, even with synthetic data, to validate feasibility and demonstrate ROI before broader rollouts. This process builds both internal expertise and functional confidence, allowing utilities to scale what works. 

We also help utilities evaluate and prepare their real operational data in parallel, so successful pilots can smoothly transition into production. 

We partner with clients to identify practical, high-value AI use cases tailored to their operations, whether they’re in generation, transmission, distribution, or natural gas. Examples include: 

• SCRAM Predictors and Reactor Health Monitoring – Forecast potential emergency shutdowns using AI analysis of reactor conditions 

• Outage Optimization – Use historical outage data and AI models to improve critical path planning and reduce schedule variance 

• Automated Compliance Reporting – Streamline regulatory reporting and licensing updates using AI-powered automation 

• Drone-based Asset Inspections – Apply AI and computer vision to detect corrosion, vegetation encroachment, and structural issues on towers and poles 

• Grid Load Optimization – Use AI to balance load and optimize flows in real time, improving reliability and reducing losses 

• Predictive Maintenance – AI-driven models detect failing transformers and substations before they cause outages 

• Pipeline Health Monitoring – AI models analyze sensor data to detect leaks, corrosion, and integrity risks along pipeline systems 

• Work Order Optimization – AI-assisted scheduling tools prioritize maintenance work based on asset condition and risk factors 

• Gas Demand Forecasting – Predict short-term and seasonal gas demand fluctuations using AI-enhanced modeling 

• Corrective Action Program (CAP) Automation – AI streamlines incident investigation, classification, and resolution tracking, reducing manual work 

• Supply Chain Optimization – Predict demand for critical equipment, optimize procurement timing, and identify supplier risks 

• OT Cybersecurity Enhancements – Combine physical sensor data with network monitoring to improve anomaly detection and reduce false positives