Funding for robotics has slowed broadly since its peak in 2021-2022, but many of the problems exposed by the pandemic remain. The biggest push behind financing projects in this category is the ongoing labor shortage. Garner analyst She expects this to happen by 2028Half of large enterprise companies will use robots in their warehouse and manufacturing operations.

Another key factor that warehouse and logistics robots play is a proven track record. While many automation methods currently have a theoretical ROI, warehouse robots are out there and doing the work now, from Amazon on down.

Gray or unclear issue He is among those who have a proven track record in this field. The Southern California company itself reports that its systems currently produce “a 2-4x improvement in production line productivity [and a] A 30% or more reduction in consumer waste. Big names, including 3M, are currently using their systems.

All this despite the fact that GrayMatter is a young company, having only been founded at the beginning of the pandemic in 2020.

“We founded GrayMatter to drive productivity while prioritizing workforce well-being,” says co-founder and CEO Aryan Kabir in a statement. “With our physics-based, AI-powered systems, we are achieving our mission while unlocking new levels of efficiency and productivity. With the support of our investors, we are making a real difference for store workers and addressing the critical labor shortage in today’s manufacturing sector.”

So what is a “physics-based” robotics system? GrayMatter contrasts its approach with the purely data-driven approach used by others. The company explains:

Consider the problem of predicting the output of a process based on the inputs. If the output is expected to increase as the input increases, the underlying model will have limited space and a smaller amount of data can train it. We do not need to consider arbitrarily complex models. On the other hand, this requires more complex representations and associated solution generation methods to deal with constraints to produce acceptable computational performance. We cannot train a simple neural network using observed input and output data. In this case, there is no guarantee that it will maintain operation if the output used during training is noisy.

Interest in the company has driven growth. GrayMatter is a regular member of our robotics job openings. the A roundup we published in May 20 open roles are listed, among the highest of those listed.

This growth, in turn, is supported by continued financing. On Thursday, GrayMatter announced a $45 million Series B round, led by Wellington Management, with participation from NGP Capital, Euclidian Capital, Advance Venture Partners, SQN Venture Partners, B Capital, Bow Capital, Calibrate Ventures, OCA Ventures, and Swift Ventures.

The round nearly doubles the $25 million the company closed in 2022.

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