Our goal:
reduce your raw material losses and optimise your processes

For many years, the agri-food and agricultural industry has taken an interested look at digital technologies (IoT, IA, etc.) in search of productivity gains, more constant production but also a reduction in the loss of raw materials.

It is for this purpose that we provide the expertise of our employees in data analysis, algorithms (artificial intelligence, regulation, etc.) and decision-making tools: food formulation (Nutriscore, etc.), recognition, sorting and grading of products, reduction of overdose, herd management, animal nutrition, etc.

Let’s work together !

The thorns in your side

  • excessive loss of raw materials
  • non-constant production
  • increase in musculoskeletal disorders (MSDs)
  • complex decision making
  • complicated quality control

Your major challenges

  • reducing costs
  • saving on raw materials
  • facilitating maintenance

What you will experience

  • sharing your challenges and your needs
  • collecting the “right” data without interrupting your activities
  • simulating your proocess thanks to modelling
  • using algorithms to optimise your process
  • taking advantage of a custom-developed tool
  • validating the gains made

Our references

Our jargon

  • applied mathematics, ergonomic interfaces,
  • artificial intelligence, decision-support tools,
  • industry 4.0, predictive maintenance,
  • process optimisation, big data,
  • Matlab, Python, R.

In practice

Meal preparation to the nearest gram!

In the agri-food industry, the weight displayed on the packaging must meet specific requirements (TU1, TU2, etc.) in accordance with the regulations

Machine learning thanks to neural networks

The principle of a neural network is to schematically reproduce the human brain and its way of associating items so as to automatise the process into a machine : it is commonly called artificial intelligence.