Industrial
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Generic AI wasn't built for the complexity of a modern energy portfolio — mixed generation fleets, intermittent renewables, and a wide range of asset types. IRIS Foundry, Forge, and Flows apply AI that understands energy operations specifically, so teams get from data to decision in weeks, not quarters.
Generic AI wasn't built for the multivariable complexity of a modern energy portfolio — mixed generation fleets, intermittent renewables, and asset types that span generation, storage, and grid. IRIS Foundry closes that gap with domain intelligence built around energy operations, so insight doesn't wait for a data science team to catch up.
From renewable intermittency to fragmented plant data, IRIS Foundry addresses the real operational pressures across generation, storage, and grid.
Mixed generation fleet complexity
Thermal, renewable, and storage assets each behave differently, leaving generic AI models unable to keep up with a fleet that spans multiple technologies and vintages.
Renewable intermittency
Solar and wind output shifts with weather and time of day, complicating planning and making it harder to forecast generation against demand.
Asset reliability across generation and grid
Turbines, compressors, and transmission equipment fail without warning, risking capacity factor and grid reliability when unplanned downtime hits.
Battery and storage degradation
Storage assets lose performance gradually and often invisibly, until degradation shows up as reduced capacity exactly when it's needed most.
Fragmented plant and field data
SCADA (supervisory control and data acquisition), historians, and asset management systems rarely talk to each other, leaving teams to reconcile data manually instead of acting on it.
Manual data pulls slow response
Control room and field teams lose time pulling data by hand instead of getting straight answers about what's happening in operations.
From predictive maintenance to agentic operations, IRIS Foundry, Forge, and Flows apply one unified data foundation to the use cases that matter most across your fleet.
Predictive maintenance for rotating equipment
Continuously monitor compressors, pumps, turbines, and motors, predicting failures up to 30 days in advance and automatically triggering maintenance work orders to protect capacity factor across the fleet.
Battery and storage health
Monitor degradation and performance over the life of every storage asset, so capacity loss is visible long before it becomes a problem.
Solar and wind performance optimization
Get the most output from renewable assets already in the field, with AI tuned to your actual generation conditions.
Renewable output forecasting
Predict generation against weather and demand so operators can plan around intermittency instead of reacting to it.
Grid and transmission asset reliability
Predict and prevent failures on transmission-side equipment before they turn into outages.
Unified plant and field data
IRIS Foundry unifies IT, OT, and IoT data — historians, SCADA systems, and enterprise platforms — into one governed foundation, without requiring you to replace the infrastructure you already run.
AI assistant for control room and field teams
Get a live view of SCADA and DCS (distributed control system) data with interactive alarm rationalization and remote expert support, cutting response time to process upsets for control room and field teams.
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Planned outage and turnaround intelligence
Coordinate work scope, inspection findings, scheduling, and materials availability across planned outages and turnarounds — compressing duration, controlling cost overruns, and ensuring a safe return to service.
One unified data foundation, one way to build new AI applications, and one layer of agentic execution, built to work together across your fleet.
The data foundation that unifies data across generation, storage, and grid assets so every other use case has something reliable to run on.
Talk to an expert who knows energy operations — not just industrial AI.
