Industry · Food & beverage

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.

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Improve quality & yield →Reduce energy & emissions →Optimize throughput →
BATCH · dryer_Bsoft-sensor v2
Predicted lab quality vs target — in band

Industry reality

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.

Top use cases

The work that pays for itself first.

Use case 01Open solution →
ProblemDryer batches land off-spec on moisture or temperature.
AI approachSoft sensor predicts end-of-batch quality from inlet conditions.
KPI improved+2.1pp first-pass yield
Use case 02Open solution →
ProblemRefrigeration runs harder than it needs to at night.
AI approachForecast cold demand and optimize compressor staging.
KPI improved−7% refrigeration kWh
Use case 03Open solution →
ProblemGiveaway eats margin on filling lines.
AI approachPredict and trim overweight events in real time.
KPI improved−1.2% giveaway
Use case 04Open solution →
ProblemCIP issues spotted only after a failed swab.
AI approachAnomaly model on CIP cycle signatures (temp, flow, conductivity).
KPI improvedFewer reworked batches

Relevant product modules

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.

Customer proof

Nordic Foods AS

Food & beverage · Scandinavia

“Our dryer team now adjusts setpoints when Intelecy flags drift — not when QA flags off-spec.”
— Plant manager, dryer line

Headline result

+2.1pp

first-pass yield, dryer line

Data & integration

What we read, how often, and how it gets here.

Common systems

Historian, MES, LIMS, PLC/DCS for drying and refrigeration

Common tag classes

inlet/outlet temp, humidity, moisture, flow, weights, energy meters

Sample rate

1–10s for process; per-batch for lab and recipe

Integration notes

Historian + LIMS export via Gateway. Recommendations in workspace or pushed to HMI.

Compliance & sustainability

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.

For your internal champion

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.

Download one-pager (PDF)Email it to your team

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.

Book industry demoTalk to a food specialist