There is no shortage of companies trying to make industrial activities more efficient with artificial intelligence. Some businesses use machine learning to help them discover insights, while others use robots to assist or replace manual labor. The second category includes Synergies Intelligent Systems.
Michael Chang founded Synergies in Boston in 2016 to provide easy-to-use analytics tools to medium-sized manufacturers. Chang realized that not every factory has the financial ability to spend tens of thousands of dollars on digitization after working at a factory that helped the Apple supplier improve yield rate or reduce the percentage of defects.
The company was mostly bootstrapping during its early years, but recently accepted venture funding to accelerate hiring, market expansion, and product development. It secured $12 million from a Series A funding round led by N GP Capital, which was formerly called Nokia Growth Partners. New Future Capital is a private equity firm.
Synergies now has a team of about 70 employees in six different countries.
80% of the startup's customers are in Greater China, including mid-sized factories with thousands of workers run by Fuyao, one of the world's largest auto glass producers. The pair doesn't have a large-scale partnership yet, but they are working on some projects in the early stages.
The telecoms titan has been promoting industrial 5G, which is to bring next-generation connectivity to manufacturing. The two will work more closely together in the future.
The product could work well with 5G-powered factories that are constantly collecting and analyzing data in the cloud. It provides a platform to help manufacturers maximize efficiency on three fronts.
By analyzing operational data, Synergies's software can make suggestions to managers, for example, suggesting how much supply they should procure, or how to quickly change a product line to maximize capacity at the lowest cost. Once the advice is put into practice and the data is collected, machine learning systems can analyze and keep refining its algorithms to help factories improve performance.
For an average small and medium-sized factory in China, the overhead for creating a comprehensive data middle platform is too high.
Most small and medium factories only have a small team of IT staff and no dedicated scientists.
Chinese factories have been around for four or five decades. They want quicker returns on investment and operate at lower margins. It's hard to get them to spend $10 million on a data platform.
The problem of high turnover in the manufacturing industry is addressed by using data analytics and artificial intelligence. As population growth slows in China, factories are struggling to recruit and retain workers, meaning it is hard to retain workplace knowledge.
It isn't a business that sees the kind of crazy growth as a coin company.
China’s Black Lake raises $77M to give factories a digital upgrade
All Rights Reserved © 2024
