Energy & Utilities
Connecting distributed energy sites
into a single intelligence layer
Data scattered across SCADA, EMS and smart meters is connected through an ontology, and an AI agent catches anomalies first and explains the cause. From unified control to predictive maintenance and automated ESG reporting.
These are the problems on
energy and utility sites today
- The data sits apart
- Seeing the whole picture at once is difficult
- SCADA, EMS and billing hold separate records
- Failures are known too late
- Anomalies surface only after a stoppage
- Little room to act preventively
- ESG and regulatory reports are manual
- Emissions figures are gathered by hand
- Reporting takes time and invites error
- Real-time response lags
- Demand, tariffs and weather move faster than the response
- Every judgment spans several screens
This is how
Refinery solves it
Unified control of distributed assets
- Problem
- SCADA, EMS and meter data kept apart, with no integrated view
- Approach
- Field data is connected through an ontology, defining assets, grids and locations in one structure.
- Outcome
- Status and alarms for generation, T&D and consumption, live on one screen
Predictive maintenance
- Problem
- Response only after an anomaly has grown into a stoppage or incident
- Approach
- Patterns that differ from the norm are learned from time-series data to catch early signs.
- Outcome
- Fewer unplanned stoppages and less downtime by acting before failure
Energy efficiency and peak optimization
- Problem
- Waste and demand charges built up by invisible consumption patterns
- Approach
- Consumption is analyzed by asset and segment, with adjustments proposed against tariff and demand signals.
- Outcome
- Lower operating cost from reduced peaks and better efficiency
Automated ESG and carbon reporting
- Problem
- Manual aggregation of emissions and consumption for regulatory reports
- Approach
- Emissions and consumption metrics are aggregated automatically from field data and turned into reports.
- Outcome
- Regulatory reports produced automatically, traceable to their source
Real-time anomaly detection and alerts
- Problem
- Anomalous signals missed, or noticed too late
- Approach
- An AI agent detects anomalies in live data and proposes both the likely cause and the next action.
- Outcome
- Early recognition of problems, with an evidence-backed next step in hand
How it fits together
How field data gains meaning and turns into a decision.
- Generation
- substation assets
- smart meters
- sensors
- SCADA
- EMS
- Modbus
- OPC UA
- DNP3
- IEC 61850
- Ontology
- AI agent
- rules and automation
- Unified dashboard
- alerts
- ESG reports
Where SCADA or EMS already exists, a layer sits on top of itand integrates bidirectionally rather than replacing it.Where none exists, collection is built from the ground up.
Systems we connect to
The systems and protocolscommonly used on energy sites.
Systems not listed here can still be connectedover standard protocols and APIs.Get in touch and we will walk through it.
What you gain
Benefits across operations, engineering and management.
Early anomaly detection
Signals that differ from the norm are caught in real time, reducing stoppage and incident risk.
Unified control
Distributed assets and grids are monitored on one screen and in one structure.
Energy efficiency
Consumption patterns reveal waste and peaks, cutting operating cost.
ESG automation
Emissions and consumption reports are aggregated automatically, with sources traceable.
Site security
With on-premises deployment, data does not leave your network and the OT/IT boundary stays protected.
Integrate or build new
Where legacy SCADA, EMS or ERP exists, Refinery layers on top and integrates bidirectionally. Where none exists, it is built from scratch.
