Covariant
Machinery : Industrial Robot : Piece Picking
Since the first industrial robots were introduced in the 1960s, millions have been deployed globally. Their impact is undeniable. Robots have automated countless dangerous, repetitive tasks, transforming manufacturing, but they’ve only reached a fraction of their potential. Incapable of thinking on their own, they can only do pre-programmed tasks in tightly-controlled environments. They can’t understand, learn, or adapt.Building on our experience at Berkeley and OpenAI, our vision is the Covariant Brain: universal AI that allows robots to see, reason, and act on the world around them. We’re bringing the Covariant Brain to commercial viability, starting with the industries that make, move and store things in the physical world.
Assembly Line
Our universal AI, the Covariant Brain, powering ABB and Fabuc robots simultaneously
Covariant raises $75M for its AI-powered warehouse robots
Covariant, a startup developing warehouse robots that can be deployed faster than traditional automation hardware, has raised $75 million in funding. The company disclosed the investment today. The capital was provided as an extension to a Series C round that it had originally announced in 2021. Radical Ventures and Index Ventures co-led the new investment, while five other institutional backers contributed as well.
Radial Selects Covariant to Automate eCommerce Fulfillment with AI-Powered Robotics
Radial, Inc., a bpost group company, the leader in eCommerce solutions, today announced a new partnership with Covariant, a leading global AI Robotics company, to automate sortation in their batch-picking operations through the installation of twelve Covariant Robotic Putwalls. The Robotic Putwalls sort a high variety of health and beauty items for one of the world’s leading retailers in Radial’s fulfillment center in Louisville, Kentucky.
The integration of Covariant’s Robotic Putwalls into the existing facility operations delivers more optimal eCommerce fulfillment performance and accuracy – providing high quality, reliable and consistent customer experience for Radial’s clients. With a more automated order sortation system, Radial can reduce worker strain and fill gaps in its workforce, while improving overall facility output and delivery times, specifically around high-demand periods.
Covariant Robotic Depalletization | Mixed-SKU Pallets
Covariant Robotic Induction Sizzle Reel
KNAPP and Covariant Partnership Advances AI Robotics for more Efficient Warehouses
KNAPP, technology partner for intelligent value chains, and Covariant, a leading global AI robotics company, strengthen their partnership to further develop AI-powered robot solutions and expand their market presence. So far, KNAPP and Covariant have successfully implemented multiple projects together, with KNAPP’s picking robot – the Pick-it-Easy Robot – at the forefront of their endeavors. The robot’s ability to handle a wide range of items and suitability for various sector applications have proven their value in improving warehouse efficiency across numerous industries.
Robotic Flexibility: How Today’s Autonomous Systems Can Be Adapted to Support Changing Operational Needs
While robots are ideally suited to repetitive tasks, until now they lacked the intelligence to identify and handle tens of thousands of constantly changing products in a typical dynamic warehouse operation. That made applying robots to picking applications somewhat limited. Therefore, when German electrical supply wholesaler Obeta sought to install a new automated storage system from MHI member KNAPP in its new Berlin warehouse as a means to address a regional labor shortage made worse by COVID-19, the company specified a robotic picking system powered by onboard artificial intelligence (AI).
“The Covariant Brain is a universal AI that allows robots to see, reason and act in the world around them, completing tasks too complex and varied for traditional programmed robots. Covariant’s software enables Obeta’s Pick-It-Easy Robot to adapt to new tasks on its own through trial and error, so it can handle almost any object,” explained Peter Chen, co-founder and CEO of MHI member Covariant.ai.