No-code Industrial AI for food and beverage processors.
Same recipe, different result — and QA confirms the problem hours after the batch is already off. Energy in drying and refrigeration adds up shift after shift.
The operating pressures we built around.
Product variability
Raw material moisture, fat, and composition shift batch to batch.
Hygiene & changeovers
CIP and allergen changeovers cost real shift hours.
Energy in drying & refrigeration
Dryers, chillers, and freezers dominate the energy bill.
The work that pays for itself first.
The platform capabilities that matter most here.
- Model builder →
Soft sensors are the workhorse here — drying, mixing, fermentation.
- Forecasting →
Batch end-state and cold demand.
- Prescriptive optimization →
Setpoint guidance for operators on critical lines.
Nordic Foods AS
"Our dryer team now adjusts setpoints when Intelecy flags drift — not when QA flags off-spec."
What we read, how often, and how it gets here.
Historian, MES, LIMS, PLC/DCS for drying and refrigeration
inlet/outlet temp, humidity, moisture, flow, weights, energy meters
1–10s for process; per-batch for lab and recipe
Historian + LIMS export via Gateway. Recommendations in workspace or pushed to HMI.
Reporting and audit, built into the workflow.
Food safety (HACCP / FSMA / EU 178/2002)
Recipe and setpoint history available for audit per batch.
Allergen and changeover traceability
Every model recommendation tagged to line, batch, and operator.
ESG reporting
kWh and CO2 per ton of finished product, verified against baseline.
One-pager for food & beverage teams.
A printable summary covering the use cases, expected KPIs, data needed, and integration notes on this page — written for plant leadership and IT/OT.
See it on your own food & beverage data.
A 30-minute working session with an industry specialist. Bring one unit and your top KPI — we'll come back with a working model proposal.