US startup raises $45 million in Series B funding

Use "AI+ Robots " to solve the labor shortage problem?

With the rapid development of AI and automation technologies, the manufacturing industry is facing unprecedented opportunities and challenges.

On the one hand, new technologies provide great possibilities for improving production efficiency, reducing labor costs, and improving product quality; on the other hand, problems such as the shortage of skilled workers and the rising demand for production flexibility have also brought considerable pressure to manufacturers. How to make full use of technologies such as AI and robots to solve actual production problems has become the focus of the industry.

While workers are wondering whether AI and robots will replace their jobs, Los Angeles-based GrayMatter Robotics has proposed a new perspective on the plight of the US manufacturing industry: the current problem is not a lack of jobs, but "not enough staff", with too few people doing too much work.

Recently, this startup company, whose mission is to "improve human productivity and improve the quality of life" and is committed to helping humans complete tedious tasks through "AI + robots", officially announced the completion of a US$45 million (approximately RMB 330 million) Series B financing.

It is reported that this round of financing was led by Wellington Management, with participation from 11 well-known institutions including NGP Capital, Euclidean Capital, B Capita, Advance Venture Partners, SQN Venture Partners, 3M Ventures, Bow Capital, Calibrate Ventures, OCA Ventures and Swift Ventures.

The funds raised in this round will be used to expand the scale to meet customer needs and help the company grow. After the completion of this round of financing, the total amount raised by GrayMatter so far has exceeded US$70 million (approximately RMB 500 million).

GrayMatter Robotics: Using AI to solve manufacturing pain points

GrayMatter Robotics was founded in 2020 by USC (University of Southern California) alumni SK Gupta, Brual Shah and Ariyan Kabir. The company's core business is the design and production of autonomous robotic arms and the development of artificial intelligence models to program them, and its core competitiveness lies in this.

GMR-AI?: A breakthrough in physical intelligence

Unlike traditional industrial robots that require complex programming, GrayMatter's robots can autonomously learn and adapt to different production tasks through AI algorithms, greatly reducing the threshold for deployment and use.

GrayMatter's core technology, GMR-AI?, is an artificial intelligence system that combines physical models and machine learning. It can use physical laws and process knowledge as constraints to guide the learning process of the AI ​​model, thereby achieving rapid adaptation to complex manufacturing environments while ensuring safety and explainability.

For example, in a grinding task, GMR-AI will use the material mechanics model to predict the relationship between processing pressure and surface deformation, and then continuously optimize the control strategy based on actual processing data. This enables the robot to master complex processing skills in a short period of time and have good generalization capabilities.

Autonomous programming: the transition from “teaching” to “learning”

Traditional industrial robots require professional engineers to perform tedious programming and debugging, and often take weeks to be put into use. GrayMatter's robots can complete autonomous programming in just a few minutes, achieving "plug and play".

Its proprietary GMR-AI? technology enables robots to self-program and adapt to high-mix manufacturing environments, delivering consistent quality and reducing cycle times. In the past two years, GrayMatter Robotics has deployed robots in aerospace, defense, specialty vehicles, marine, entertainment and general manufacturing in North America, processing more than 7.5 million square feet of product surface area and holding 10 patents.

Multi-field application: full coverage from polishing to testing

GrayMatter's technology is not limited to a single application scenario. At present, its product line has covered multiple manufacturing links such as grinding, polishing, spraying, coating, finishing, and testing. This comprehensive coverage capability enables GrayMatter to provide customers with more integrated and systematic automation solutions.

RaaS: Making Smart Manufacturing Within Reach

In addition, the company adopts the "Robot-as-a-Service" (RaaS) model, which greatly lowers the usage threshold for customers and accelerates the popularization of intelligent manufacturing technology.

We often think that implementing robotic solutions requires a large upfront investment in infrastructure and expertise. Kabir, the company’s co-founder, also said: “This is true, but it is not the case for customers who use GrayMatter Robotics to automate because, unlike most customers, we are able to do it using a Robotics as a Service (RaaS) model.”

Traditional industrial robots often require customers to invest a large amount of money in one go to purchase equipment, which is a considerable burden for many companies. GrayMatter uses generative AI to customize each project according to specific needs. This model reduces the initial investment of customers and is more friendly to small and medium-sized enterprises.

The RaaS model also enables GrayMatter to collect a large amount of production data, providing a basis for further technological innovation and optimization. By analyzing usage data from different industries and different customers, GrayMatter can continuously improve its AI algorithms and develop more intelligent and universal manufacturing solutions.

In the long run, this data-driven approach is expected to become one of GrayMatter’s core competitive advantages.

Last words

The U.S. manufacturing industry is facing severe challenges.

According to data, due to labor shortage, this $2.5 trillion industry is facing a serious backlog of orders, with as many as 3.8 million job vacancies, which not only affects production efficiency, but also directly threatens whether companies can deliver on time.

There are many factors that lead to this problem, including demographic changes, skills gap, social environment, etc. However, if the manufacturing industry, as the economic pillar of the United States, cannot effectively solve the labor shortage problem, then by 2030, the US economy may face the risk of losing $1 trillion a year.

GrayMatter's technology provides a solution to alleviate this problem.

The company’s robots work 2-4 times faster than manual operations, and what would normally take six months for humans to train now takes less than a day. In addition, compared with traditional methods, they can reduce consumable waste by 30% or more and reduce energy consumption, helping companies achieve their sustainability goals.

GrayMatter's technology is also changing the nature of work for manufacturing workers. Traditional surface treatment work is often characterized by repetitiveness and harsh environments, and GrayMatter's robots can take over these tasks, allowing workers to turn to more creative and technical work. As GrayMatter CEO Ariyan Kabir said: "Our goal is to increase productivity while prioritizing employee well-being."

However, although GrayMatter's technology has lowered the threshold for use, workers still need to master new skills to fully realize its potential. For example, how to collaborate with AI systems, how to interpret and use data analysis results, etc. This requires manufacturing companies to increase investment in training to help employees adapt to the new requirements of the AI ​​era.

According to a report from IBM, as AI becomes more common in the workplace, 40% of employees will need to be retrained. But AI-centric jobs also pay 77% more than other occupations. According to Bizreport data, the average salary for machine learning researchers in Arkansas is $409,877, while engineering managers in California make $406,949 per year.

In general, traditional automated production lines are often only suitable for large-scale, standardized production, while GrayMatter's robots can quickly adapt to different product and process requirements, which makes small-batch, customized production more economical and feasible, helping manufacturers better meet market demand.