Client: JSC Grainmore
Industry: Oat processing, flakes & granola manufacturing
Location: Lithuania
Solution: GrainODM AI-powered grain quality inspection system
1. About JSC Grainmore
JSC Grainmoreis one of the most advanced oat processors in Northern Europe, producing oat flakes, groats, and granola bases for leading food brands worldwide.
At this scale, consistency and purity of raw oats directly determine product quality — from breakfast cereals to granola bars.
Traditionally, grain inspection relied on manual visual checks that were slow, subjective, and labor-intensive.
To meet growing demand and maintain uncompromised quality, Grainmore turned to automation.
2. The Challenge
Manual grain sorting required up to 20–30 minutes per sample and depended heavily on operator experience.
During peak harvest periods, hundreds of samples arrived daily, creating laboratory bottlenecks and risking delays in production.
Grainmore needed a faster, objective solution capable of:
- ensuring consistent results between shifts and operators,
- providing instant sample traceability,
- and being simple enough to operate directly on the production floor.
3. The Solution — GrainODM AI Inspection System
Grainmore implemented the GrainODM system — a computer-vision solution designed to analyze oat samples automatically.
The system uses an industrial-grade camera with controlled LED lighting and AI algorithms trained to detect and classify oat kernels, flakes, and impurities in seconds.
Key features
- Automatic image capture and analysis – the operator simply loads a sample and presses Scan.
- AI-based classification of good oats, unhulled kernels, husks, dark grains, and foreign particles.
- Instant visual report – defects are color-coded directly on the analyzed image.
- Digital data export – results are stored automatically for traceability and trend tracking.
The system was designed to be operator-friendly, requiring minimal training and ensuring consistent results across all production shifts.
4. Results
After deploying GrainODM, Grainmore achieved a dramatic improvement in speed and repeatability.
| Metric | Before | After GrainODM |
|---|---|---|
| Sample analysis time | 15–25 min | 15–20 s |
| Operator dependency | High | Low – one-button operation |
| Repeatability | Medium | Consistent across shifts |
| Traceability | Manual notes | Automated digital reports |
| Training time | Several weeks | Under 1 hour |
The laboratory team now validates sample quality in real time, and production managers can access photo-based reports immediately after each analysis.
This improvement transformed sample analysis from a bottleneck into a continuous, integrated part of the production flow.
At first, employees were checking the system. Now the system ensures that the employees work correctly.
— JSC Grainmore representative
5. Impact on Oat and Granola Production
By automating the inspection process, Grainmore:
- eliminated subjective evaluation errors,
- ensured uniform appearance and purity of oat flakes and granola ingredients,
- reduced testing time from minutes to seconds, and
- built a consistent digital archive of every batch.
The new workflow strengthened supplier transparency, improved customer confidence, and supported the company’s sustainability goals by minimizing waste and rework.
6. Conclusion
The Grainmore case shows how AI vision can bring measurable efficiency gains to oat and granola production.
Replacing manual, time-consuming inspection with automatic analysis reduced testing time by 75× while delivering consistent, traceable results.
Grainmore now combines speed with accuracy — setting a new benchmark for quality control in the oat processing industry.
From 25 minutes to 20 seconds. From manual checks to automated precision. This is how modern oat production achieves consistency with GrainODM.
— Lukas Vaznelis, BDM
Interested in similar results for your grain processing operation? Contact our team to discuss how GrainODM can help optimize your quality control processes.
Frequently Asked Questions
AI vision replaces manual inspection with automated image analysis that detects unhulled kernels, husks, dark grains, and other impurities in seconds. This ensures objective, repeatable results while freeing operators from repetitive visual checks.
Yes. GrainODM models are trained to recognize multiple oat product types — from raw unhulled oats to stabilized flakes used in granola. The system automatically adapts its classification logic to the selected product profile.
Each inspection generates a digital report that includes the analyzed image, defect statistics, and batch details. The results are securely stored and can be exported for quality documentation, supplier reports, or trend monitoring.
Minimal. Operators learn to use the system within an hour. The interface is intuitive — simply load the sample, press Scan, and the results appear automatically.
Yes. The system allows retraining with new sample images to continuously improve recognition accuracy or add new product types. Model training is fully integrated within the GrainODM software — no external tools or programming knowledge are required. This ensures long-term adaptability to evolving production lines.
The New Standard in Grain Purity Testing
Data, not guesswork. Learn how GrainODM sets a new benchmark for digital grain inspection.