There is no shortage of startups around the world to make industrial operations more efficient through artificial intelligence. Some are inventing robots to help or replace manual labor, while others are using machine learning to help companies discover information. Synergies Intelligent Systems belongs to the second category.
Michael Chang founded Synergies in 2016 in Boston to provide easy-to-use AI-based analytics tools to midsize manufacturers. Having worked at Foxconn in Shenzhen in the late 2000s to help supplier Apple improve yield rate or reduce the percentage of defective products, using data analysis, Chang realized that all factories couldn’t afford to spend tens of thousands of dollars on digitization.
Synergies’ vision and recent growth have won support from investors. The company was mostly start-up in its early years, but recently accepted venture capital funding to accelerate hiring, market expansion and product development. It secured $12 million in a Series A funding round led by NGP Capital, which was previously called Nokia Growth Partners and is backed by Nokia, as the name suggests. Private equity firm New Future Capital also participated.
Synergies now operates a team of approximately 70 employees in Shanghai, Taipei, Guangzhou, Singapore and Boston.
The startup declined to disclose its valuation, but said it serves nearly 100 customers, 80% of which are in Greater China, including medium-sized factories with thousands of workers run by Foxconn and Fuyao. one of the largest automotive glass producers in the world. Chang told TechCrunch that Nokia and Synergies are working on some early-stage projects, though the pair don’t have a full-scale partnership yet.
The Finnish telecommunications titan, as far as Chang knows, has been promoting “industrial 5G” around the world, which is to bring next-generation connectivity to manufacturing. So it won’t be surprising to see the two working more closely together in the future.
Synergies’ product could work well with 5G-powered factories that constantly collect and analyze data in the cloud. It provides what is called an “augmented analytics” platform to help manufacturers optimize efficiency on three fronts: supply chain, yield and production capacity.
By analyzing operational data, Synergies’ software can make suggestions to managers, such as recommending how much supply they should buy or how to quickly change a product line to maximize capacity at the lowest cost. Once the advice is put into practice and new data is harvested, Synergies’ machine learning systems can analyze and continue to refine their algorithms to help factories improve their performance.
“Such machine learning is not rocket science for AI experts, but for an average small to medium-sized factory in China, the overhead of building a complete ‘data middleware platform’ is too high because they require coordination between IT, project managers, and AI experts,” suggested Chang, an MIT graduate with a Ph.D. in electrical engineering and computer science.
“Most small and medium-sized factories only maintain a small team of IT staff, let alone a team of dedicated AI scientists.”
“Compared to advanced manufacturers in the West,” Chang continued. “Chinese factories, even the massive ones today, have only been around for four or five decades. They are much more price sensitive, operate with lower margins and want faster returns on investment. It is therefore difficult to ask them to spend 10 million dollars upfront to build a data platform.
Using data analytics and AI to refine business decisions also solves the problem of high turnover in the manufacturing industry, Chang explained. As population growth slows in China, factories are struggling to recruit and retain workers, which means it’s also difficult to retain knowledge in the workplace.
“It’s not a company that’s having the kind of crazy growth that, say, crypto companies have,” Chang argued. “But I believe it’s a meaningful undertaking because we’re creating real change on the ground.”