Reduce energy use and emissions with no-code Industrial AI.
Energy targets and CO2 reporting are now operational concerns. Intelecy quantifies the most efficient operating point per unit and keeps it there as conditions change.
What makes this operationally expensive today.
Energy cost volatility
Spot prices and grid signals change faster than control strategies.
CO2 targets and compliance
Reporting needs auditable baselines and verified savings.
Process inefficiency
Conservative setpoints quietly burn extra fuel and steam, shift after shift.
The process indicators behind every recommendation.
Intelecy reads these signals from your Historian, DCS, and SCADA — no new sensors required to get started.
From signal to action, mapped to the modules.
- STEP 01Data Explorer →
Establish a true baseline
Normalize energy use against load, ambient, and recipe — not against last year.
- STEP 02Forecasting →
Forecast demand and price
Project unit load and grid signals so operators run heavy loads at the right window.
- STEP 03Prescriptive optimization →
Optimize the operating point
Recommended setpoints that minimize kWh/ton while holding quality and throughput.
- STEP 04Energy monitoring →
Report verified savings
Every kWh and kg of CO2 saved is tied back to the baseline and exportable for audit.
How customers measure success.
European utilities operator
"We can finally show finance and ESG the exact kWh we saved this quarter, traceable back to the setpoint change."
What it takes to stand this up.
Energy meters, production counters, and key process tags per unit. Optional weather and price feeds.
Baseline and first optimization live within 3–4 weeks.
Energy manager, process engineer, sustainability lead, finance for verification.
Historian + utility meters via the Gateway. Reports exportable to ESG tooling.
See it on your own plant data.
A 30-minute working session with our process AI team. Bring a unit, a goal, and a few tags — leave with a working model proposal.