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Manufacturers face many confusing issues around the machinery they manufacture, and it’s challenging to keep track of issues. This is just not good to know. It is critical information that is tracked manually in a spreadsheet by human auditors today. In some cases, not knowing when there is a faulty part can lead to costly recalls and, in more severe cases, death and lawsuits.
Enter Stock RayAn early stage startup is tracking unstructured data using machine learning to build a picture of potential problems before these issues spiral out of control. Today, the company announced a healthy $7.5 million seed round.
“What we’ve done is build a new artificial intelligence platform that can help manufacturers stay ahead of major threats like recalls by tapping into unstructured data and developing new ways that haven’t really been tapped to this point,” StockRay co-founder and CEO Daniel First told TechCrunch.
He says the unstructured data comes from human users and differentiates his organization from its predecessors.
“With traditional machine learning and many of the companies before us, most of the focus in manufacturing was on installing cameras on the manufacturing line or looking at sensor data to predict engine failure in highly structured data sets.
But the interesting thing about stocks is that we can use a huge amount of unstructured data. [chatter] Much of the information comes from the service or dealer networks, where it is technician observations, and is available through comments and issues and troubleshooting from people.
He worked as a McKinsey consultant for several years before starting the company, and saw first-hand how manufacturers were struggling to identify potential problems before they exploded. He also noticed that technicians working on these machines were seeing problems months before the companies realized there was a wider issue, and the idea for Stock Ray began to take shape.
“It became clear that there is a huge opportunity to identify and identify early warning indicators, and this could help people realize that there are risks months in advance.”
The company It was founded in 2021 and is already working with clients such as Boeing, Penn Engineering and Cummins. First, he didn’t want to share the number of customers yet, but it’s clear that some big players are interested in what his company is doing.
The startup, which has about 20 employees, is hiring mainly engineers and employees with expertise in machine learning. He says building a diverse workforce is a top priority from the start.
Even though we’re a small team, we’ve dedicated full-time colleagues from day one who are responsible for building diverse candidate pipelines and hiring practices. We are thrilled to be partnering with Inspeed Capital, one of the largest women-led venture capital funds in the country.
Today’s $7.5 million investment was led by Inspeed and Amplo, along with Boeing, Tinicum Venture Partners and industry angels.
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