Energy & Trading
Market Edge
Optimizes BESS and solar assets while supporting energy trading to turn flexibility into a revenue stream.

ADRANTOR Energy turns industrial energy complexity into controlled business value, combining ML forecasting, deterministic MPC, digital twins, BESS/PV optimization, and energy trading support.
Built for energy-intensive industrial sites that need to reduce costs, monetize flexibility, protect critical assets, and align production with market signals.
Predict. Control. Execute.
Generic energy management is no longer enough. ADRANTOR Energy is built around each site's unique production reality. It does not only monitor energy; it predicts, controls, and executes optimization decisions across operations and markets.
Advanced ML predicts plant consumption and PV generation using weather, production context, and historical process data.
Auditable Model Predictive Control turns forecasts into optimized schedules while respecting battery, grid, production, and safety constraints.
Supports participation in spot and balancing markets to monetize flexibility and reduce net energy procurement costs.
Business Impact
Our Digital Twin First approach validates the business case before major hardware investment. The platform models your real site constraints, forecasts flexibility, and simulates optimization strategies before deployment.
30-40%
Target Cost Reduction
< 3 Years
Average Payback Period
Unified control layer
ADRANTOR Energy acts as a unified data and control layer, ensuring energy economics, machine health, and shop-floor operations work in synergy.
Energy & Trading
Optimizes BESS and solar assets while supporting energy trading to turn flexibility into a revenue stream.
Machine Health
Uses vibration, acoustic, and electrical signal analysis to detect leading indicators of failure before downtime occurs.
Operation Planning
Aligns production schedules with market price signals, raw material availability, and grid constraints.
Predictive care
The platform protects core production assets by analysing vibration, acoustic, and electrical signals. ML models detect early signs of mechanical and electrical failure before they cause unplanned downtime.
Detect bearing wear, imbalance, and abnormal machine behaviour before catastrophic failure.
Monitor motor health, power quality, and electrical patterns to prevent winding issues and operational disruptions.
Plant hub
ADRANTOR Energy makes disparate systems talk to each other, creating a customer-centric operational hub for energy, production, maintenance, and market participation.
ML learns how process inputs affect throughput, quality, and energy per unit.
Energy-heavy runs can be scheduled during low-cost or high-reward market periods.
Core logic runs onsite, keeping operational knowledge secure and autonomous.
The more data the platform ingests, the smarter the optimization becomes.
Phased implementation
A staged path validates the value case first, then expands into local edge integration, predictive care, and production-aware control.
Step 01
Baseline & ROI Validation
Step 02
Sizing & Strategy Selection
Step 03
Local Edge Integration
Step 04
Predictive Care & Full Process Optimization
Every MPC schedule and ML model is custom-trained on the site's specific constraints. ADRANTOR does not sell a generic energy box; it creates a digital twin of your operational excellence.
Customer-specific optimization
Auditable control logic
Secure onsite intelligence
Production-aware energy decisions
Designed for critical industrial environments
Future proofing
Reserved space for pilot evidence, reference architectures, and customer-specific case studies as deployments mature.
Ready to optimize?
Start with a preliminary Site Data Assessment to understand your flexibility potential, cost reduction opportunities, and digital twin readiness.