GrayMatter Robotics Raises $45M

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GrayMatter Robotics Raises $45M
Robotics: Using physics-driven AI, robots are able to work on multiple objects without preprogramming.

GrayMatter Robotics, a Gardena-based industrial robotics startup, announced this month it raised $45 million in series B funding.

The round was led by Wellington Management, with participation from venture firms like Pasadena-based Calibrate Ventures and Manhattan Beach-based B Capital.

In total, the startup has raised $70.4 million.

GrayMatter, which was founded in 2020 during the throes of the pandemic, creates robots that can work on the cosmetic tasks in manufacturing that are normally done by human hands – sanding, grinding, polishing and coating everything from guitars and football helmets to boats and fighter jets. GrayMatter works with companies like Riddell (maker of football helmets and sporting goods), Lawrence Brothers (which make electric vehicle parts) and Patrick Industries Inc. (manufacturer of RV parts).

Robots have been successfully used in manufacturing for decades, and they’re especially prominent when companies need to work on the same type of part frequently. But if that part changes in size or material, or if introduced to new parts, those robots are no longer useful, and people take over.

“They’re very good at repeating the same thing again and again,” Ariyan Kabir, GrayMatter’s co-founder and chief executive, said. “However, 90% of manufacturing is high variability and you need adaptation. You need the ability to make decisions on the fly, take high-level instruction and adapt to the presented object.”

A dwindling workforce

Employees are becoming harder to come by, and the manufacturing industry is facing a crisis of unfulfilled jobs which could cost the industry $1 trillion in 2030, according to The Manufacturing Institute.

Manufacturing companies are having trouble attracting and retaining employees due to low pay and dangerous working conditions – employees can face respiratory issues, carpal tunnel syndrome, or shoulder and back injuries during their tenure in these factories, according to The Manufacturing Institute. As a result, manufacturing is increasingly turning to Silicon Valley for hard tech solutions.

“How do we build or develop the decision-making layer for these robots so that they can be autonomous,” Kabir cited as his company’s thesis. “So, we started developing physics-informed AI technologies.”

GrayMatter’s robots take a 3D scan of the part they need to work on and are able to sand the surface while taking into account any curves, dips and bumps on the surface.

This, Kabir says, improves the bottom line in manufacturing. The AI prevents robots from removing too much material or using too much paint, which in turn eliminates how much material the manufacturer needs to throw out or use due to quality issues.

GrayMatter is using the new funding to expand its product line, which will include a robot that can spray chemical compounds, as well as expand its marketing team to reach new customers.

A hard tech renaissance

After years of tunneling money into SaaS products, Silicon Valley is back on the hard tech train thanks to incentives from the U.S. government.

The domestic manufacturing workforce is waning, and the Biden Administration passed a slew of legislation such as the CHIPS and Science Act to promote manufacturing at home instead of in China.

Investors have taken note. In 2020, manufacturing robots received $39 million in global investment, per Pitchbook. The following year, that same sector saw $134 million in funding and has stayed consistent since. Manhattan Beach-based Matter Venture Partners closed a $300 million fund specifically to invest in hard tech, Tech Crunch reported in March.

“Manufacturing for the most part is very hidden. We assume everything is done magically,” Kabir said. “We need to develop a broader awareness around manufacturing and really help everyone understand what the challenges and pain points are. And we really need many more companies. One GrayMatter is probably not enough to solve the problem.”

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