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KPM Analytics

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KPM Analytics is providing analytical instrumentation primarily focused on analyzing critical parameters within the food, agriculture, clinical, and environmental sectors. 

The company offers Artificial intelligence (AI) grading and foreign material detection systems for the fruit and vegetable industry.

KPM Analytics provides critical insight and analysis for companies in the food and feed industry that strive for the highest quality standards – with their suppliers, in their finished products, and every step of the way.

From raw ingredients to prepared foods, KPM Analytics products help producers rapidly assess critical quality properties at nearly every phase of the process.

Their solutions include:

  • Lab, at-line, and in-line analyzers for measuring moisture, fat, protein, starch, and other essential quality constituents.
  • AI-driven vision inspection technologies to analyze product features at full-line speed, enable robotic sorting applications, and detect unwanted foreign materials from the processing line.
  • Flour, dough, and grain analyzers to help bakers and millers manage quality and meet consumer demands.

(Click picture to watch video)KPM Analytics – We Craft Assurance. For Our Partners. For Their Customers.

KPM Analytics – We Craft Assurance. For Our Partners. For Their Customers.

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Nieuws over dit bedrijf

Revolutionize Potato Sorting with AI: Introducing the SiftAI® Robotic Sorter
november 26, 2024

Revolutionize Potato Sorting with AI: Introducing the SiftAI® Robotic Sorter

Given the daily demands you face from customers, maintaining final potato grading precision and efficiency has never been more critical. Even when sheds are adequately staffed, defects still reach customers, or acceptable potatoes are wasted.
SiftAI® Smart Table: Multifunctional Quality Control System for Potato Packers and Processors
september 16, 2024

New AI-Based Inspection System Brings Profitability to Potato Packers and Processors

Food processors know that foreign objects and inaccurate quality grading is cutting into profits. To fix this, they have tried X-ray detection, metal detection, vision inspection systems, and large teams of human inspectors, yet success has been limited.