The past years we have mainly focused on 3 verticals. We have first built a worldwide ecosystem in agriculture where we lead with our AI software (the niche of the automated planting of plant cuttings). Farmers in Canada, Japan, Australia, USA and many other places are using RVAI technology to quickly teach in new plant types. We connect the needs of farmers (robot customers) in one continent with people in need in another continent (labelers), so direct value chains are created.

Because of this ecosystem, we have learned that robustness and ease of use are the most important aspects of self learning technology. We interacted intensively with our integrators and end customers and learned that there were secondary needs. That’s how the AI store was born.

We are now building similar ecosystems in manufacturing, smart city and medical. You can find some references below.


Agriculture is an excellent match for AI and deep learning. There are so many types of fruits and flowers, with no standard shape or size, that heuristic programming simply doesn‘t cut it. We at Robovision realised early on that it is better to invest in a machine learning configuration. Advanced neural networks are the solution here.

In this farm 24 robots are running 16 hours a day to deliver flowers to retailers all over the world. Imagine the amount of love they generate.


Robovision is at its best when serving large robotic farms like this one in Mexico City. Did you believe countries with an average monthly salary under 500$ would be a no-go for AI Robotics? Think again. AI robots guarantee a constant high quality output day and night, while allowing the workers to focus on more challenging activities . And if you‘ve installed solar panels on your roof, greasing the joints is the only remaining cost for running these robots. Pepsico invested in RVAI 1.2 for its Dorito production and is now considering using it as a standard worldwide for this type of production.


Robovision is a pioneer in person detection in complex video streams. From safety applications to processing a television stream, we start by  subsegmenting the human body in semantic parts (upper body, legs and arms, head). By doing this, we can detect particular clothing in a television show, or look for missing children with specific clothing in multiple streams. As a first in the world, we connected Genetec , the google  of surveillance, with RVAI, linking the power of deep learning to the scaling of Genetec. With RVAI FaceQuest™ we can search live streaming content from big cities for individuals with specific properties. Robovision is currently partnering up with IBM PowerAI to scale up to hundreds of realtime streams. This will allow us to open up new pilot tracks.