inVia Robotics wins innovation award
6th June 2022
inVia Robotics – a leader in eCommerce fulfilment automation systems – has been awarded this year’s Best Practices Technology Innovation Leadership Award in the North American goods-to-person robotics market by Frost & Sullivan, a leading third-party research and consulting firm.
inVia’s true robotics-as-a-service (RaaS) model beat out category competitors as it provides retailers and 3PLs with a flexible, cost-effective solution that dramatically increases productivity in existing facilities. The RaaS system allows customers to pay for productivity of inVia robots and software versus competitors who lease or sell robots. The subscription service covers all system updates and includes 24/7 monitoring and support through inVia’s Robotics Operation Center (ROC).
A team of robotics experts is dedicated to each customer to oversee fulfilment operations and troubleshoot any problems, often fixing them before they are even visible. This model democratises automation, making it available as an operating expense to businesses of all sizes, versus traditional equipment that was capital-intensive and expensive.
“We’re honoured to receive this recognition and award for our technology that is solving the pressing issues facing warehouse employees and businesses on a daily basis,” says Lior Elazary, CEO and Co-Founder of inVia. “We recognise that eCommerce demand is continuing to rise and warehouse workers are still facing immense pressures to fulfil orders quickly. Our mission is deeply rooted in creating an environment where people can do fulfilling work and in order for us to ensure this happens, we are committed to improving the technological offerings that our customers require.”
“Frost & Sullivan applauds inVia for maximising worker productivity and providing eCommerce organisations with an attainable entry point to introduce autonomous mobile robots and the PickerWall into their businesses,” says Sankara Narayanan, Industry Principal at Frost & Sullivan. “The company’s RaaS model, ROC, and quick deployment further enhance its customer value proposition.”
A key differentiator in receiving the award was the inVia PickerWall, as it demonstrates inVia’s unique workflow that removes interdependencies between robots and people and subsequently unleashes productivity rates, at a time when warehouse labour is hard to hire. The inVia PickerWall helps companies manage higher order volumes without having to increase labour enabling eCommerce warehouses to be 10 times more productive.
Most importantly, inVia PickerWall leverages the strengths of both people and robots. Robots work non-stop doing repetitive tasks like travelling and picking. People are allowed to do higher order tasks like sortation and work on a variety of tasks in bursts. Workers enjoy more stimulating working conditions and businesses enjoy consistently meeting service level agreements (SLAs) without dips in productivity.
inVia Picker robots were also recognised by Frost & Sullivan as solving one of the most challenging problems in the e-Commerce space; quick and easy access to a wide variety of stock keeping units (SKUs). E-Commerce warehouses are often 250,000 sq ft, comparable to three football fields – and may have 100,000 SKUs distributed across the warehouse. The robots are completely autonomous and eliminate the need for people to travel across the facility to retrieve inventory and deliver it to the packing station.
Additionally, inVia Pickers are mobile, unlike traditional shuttle systems, and can be moved to work in different zones or in other locations. This eliminates the need for reengineering facilities, allowing inVia to adapt to different environments.
The Frost & Sullivan Best Practices Awards recognise companies across the globe for demonstrating outstanding achievement and superior performance in leadership, technological innovation, customer service, and strategic product development. inVia was awarded based on its commitment to innovation, creativity, and application diversity that meet ever-evolving customer needs.