The primary and secondary sectors are industries traditionally accessible to automation. Through machine learning, the extension of both human capabilities and the physical means of production can significantly accelerate innovation, optimize workflows and increase productivity.


Next, we list our solutions for Manufacturing and Agriculture enterprises.


  • Reduction of equipment costs.
  • Reduction of labor costs.
  • Increase in safety.

Predictive Maintenance

It uses machine learning and real-time data gathered from equipment to notify the company's personnel when something is starting to go wrong. That way the machinery can be fixed before there is a catastrophe. This method goes beyond standard maintenance, using the actual condition of an equipment to determine when repairs should be performed.


  • Reduce labor costs.
  • Improve quality control.
  • Reduce inspection time.

Intelligent Visual Inspection

Using Computer Vision algorithms, we can automatically inspect parts, components, and products and identify defects by matching patterns to images of defects that it has previously analyzed and classified. This technology can be also used for identifying a wide variety of objects or waste and separate them from the rest of the sorting.


  • Improve land-use planning and management.
  • Reduce farmers costs.
  • Improve natural conservation.

Soil Classification for Agriculture

Computer vision can be used to analyze aerial images of land to review soil cover in great detail. It can generate analytics to monitor climate change, it can be used to prevent deforestation, provide insights to understand the impacts of urbanization, or identify opportunities to address global environmental challenges.


  • Reduction of inventory levels by 10%-30%.
  • Cost savings.

Intelligent Inventory Management

For staying competitive in today’s world, organizations need to constantly reconfigure supply chains and continually manage the changing demand and supply. Intelligent decisions in inventory management can drive large cost saves and avoid missing selling opportunities.


  • Reduce costs.
  • Improve process efficiency.

Smart Telemetry & IoT

In both manufacturing and agriculture industries, smart telemetry can be used to address technological challenges. Some examples are enabling farmers to sustainably lower costs and improve yields, intelligently detecting inefficiencies in manufacturing processes, or analyzing massive amounts of data to provide insights for decision-making.

Do you have a use case for your industry that is not listed here? Send us an email to