Machine learning, when applied properly, enables manufacturers to optimize processes, reduce emissions, reduce costs, and optimize quality. ML also assists businesses with accurate forecasting and predictive maintenance, allowing businesses to understand the impact of decisions before time and resources are spent. The data found in factories is highly valuable and easier than ever to capture but the data needs to be processed effectively to have meaningful value. Fero Labs is an industrial explainable machine learning platform that helps manufacturers unlock efficiencies by focusing on process optimization. The pandemic led to a surge in the adoption of AI solutions across industrial applications and this trend is expected to continue. Plant operators without data science backgrounds are able to implement Fero’s platform and interpret findings to add immediate value to the manufacturing process. The company, founded in 2015, grew 400% in 2020. Customers, like Henkel, Volvo Trucks, and Covestro, were able to increase profitability by 10% on average while reducing their carbon footprints.
AlleyWatch caught up with Founder and CEO Berk Birand to learn more about how machine learning is transforming manufacturing, the company’s strategic plans, recent round of funding, and much, much more.
Who were your investors and how much did you raise?
$9M Series A –led by Innovation Endeavors, with participation from Deutsche Invest VC.
Tell us about the product or service that Fero Labs offers.
Machine learning software for industrial process optimization
What inspired the start of Fero Labs?
We saw all the challenges manufacturers face, including cost pressures, increased environmental regulations, and a changing workforce. Factories have tons of data that could help them deal with these challenges—but they lack the technology to take advantage of it. We wanted to build a tool they could use to turn data into their competitive advantage.
How is Fero Labs different?
Unlike many other AI and machine learning solutions targeted at the industrial sector, Fero software is designed and built specifically for factories. A large aspect of this is explainability. We take advantage of engineers’ and operators’ domain expertise and build that into the software, giving them the confidence they need to make major strategic decisions.
What market does Fero Labs target and how big is it?
Within the broader market of industrial machine learning software, we’re focused on process optimization—helping factories become more efficient through explainable machine learning. As more manufacturers invest in Industry 4.0 capabilities, that market size continues to grow.
How has COVID-19 impacted your business?
Amid the COVID-19 pandemic and global industrial restrictions, Fero Labs grew 400% in 2020, emphasizing the increased need to create sustainable solutions for the entire industrial sector.
What are the biggest challenges that you faced while raising capital?
Our biggest goal was to find investors that were a good fit for an industrial ML company.
What factors about your business led your investors to write the check?
Manufacturing makes up the vast majority of the world’s economy. Industrial companies are ready to invest in digital technologies to improve their operations. I believe that the size of the market and the incredible traction we saw in the past year were two big factors.
What are the milestones you plan to achieve in the next six months?
We are scaling all parts of our team. Our main goal is to further improve our core technology and deploy it to more plants, across several other sectors. Our mission is to help make the industrial sector more efficient and our biggest milestone is to hit our emission reduction goals across our user base.
What advice can you offer companies in New York that do not have a fresh injection of capital in the bank?
Fundraising is always hard, even during frothy times like these. We’ve certainly been through our own episodes of fundraising issues. My recommendation is to stay laser-focused on execution, improve 1-2 core metrics, and try to cut burn to manageable levels.
Fundraising is always hard, even during frothy times like these. We’ve certainly been through our own episodes of fundraising issues. My recommendation is to stay laser-focused on execution, improve 1-2 core metrics, and try to cut burn to manageable levels.
Where do you see the company going now over the near term?
We are tremendously excited about our core R&D in Machine Learning and continue to do joint research with Columbia. In fact, our Chief Scientist Alp is an adjunct professor there.
What’s your favorite outdoor dining restaurant in NYC
La Mercerie is one of our go-to restaurants in NYC since it’s across the street from our office.
