In May we will head to Silicon Valley to be part of “TINC”, a tech incubator, at the Nordic Innovation House. The Nordic Innovation House is a collaboration among the Nordic countries and their mission is to be a “bridge connecting the cold corners of the globe with the main hotspots around the world”. The TINC program invites twice per year nine startups from the Nordic region to the Silicon Valley ecosystem.

Despite being a distributed organization across countries, we are still a close-knit group of individuals at Aivero. This past year we are happy to have welcomed Michaela, Jimmi, Isak and Daniel to our team. Bringing their areas of expertise, from engineering to marketing, increasing our ability to improve performance in research and robotics, making AI services accessible to a broader set of users. So, what does it take to translate machine vision into a plug-and-play solution for monitoring and automation?

Collaborative robots (cobots) differ on variables such as weight, payload, reach and accuracy. These set the condition for what tasks a cobot can perform, thus affecting which one is best suited for your environment. However, they all have one thing in common: they shine in their ability to perform repetitive tasks, and with Aivero Do, this is scalable across multiple units and locations.

Did you know that you might already be carrying a depth-sensing camera in your pocket? Nowadays more and more smartphones are sold with depth-sensing technology?

In observational research, the effectiveness of machine learning hinges on the quality of data. As the adage goes, “garbage in, garbage out,” high-quality data is imperative. Aivero transforms this challenge into an opportunity with its versatile software-based platform. Data Quality: The Core of Machine Learning Success Aivero’s platform stands out for its hardware-agnostic capabilities. Whether…