Manufacturers Face Dizzying Array of Potential Problems
Manufacturers face a dizzying array of potential problems around the products they produce, and it’s challenging to track down issues. This isn’t just nice to know; it’s crucial information that often gets tracked manually by human auditors in spreadsheets. In some cases, failing to understand when there is a faulty part could result in costly recalls, and in the most extreme cases, deaths and lawsuits.
Enter Axion Ray
This is where Axion Ray comes in – an early-stage startup using machine learning to track these issues in unstructured data to build a picture of potential problems before they get out of hand. Today, the company announced a healthy $7.5 million seed round.
"What we’ve done is build a new artificial intelligence platform that helps manufacturers get ahead of their major risks like recalls by tapping into and synthesizing unstructured data in new ways that up until this point haven’t really been touched," Axion Ray founder and CEO Daniel First told TechCrunch.
The Power of Unstructured Data
First explains that the unstructured data comes from human users, which separates his company from those that have come before him. "In traditional machine learning, and many of the companies that have come before us, much of the focus in manufacturing has been in highly structured datasets like installing cameras on the manufacturing line, or looking at sensor data to predict an engine failure," he says.
However, Axion Ray is leveraging huge amounts of unstructured data, such as technician observations, comments, and issues from service or dealership networks. This data is found in troubleshooting information coming from humans, which has not been touched by previous companies using traditional machine learning methods.
A Problem Recognized
First worked as a McKinsey consultant for several years before launching the company, where he saw firsthand how manufacturers were struggling to recognize potential problems before they really blew up on them. He also observed that technicians working on these products were seeing problems months before the companies realized there was a broader issue, and the idea for Axion Ray began to take shape.
"It became obvious that there was a huge opportunity to enable the detection and flagging of the earliest warning indicators," First explains, "and that could help people detect that there are risks months earlier."
The Company’s Progress
The company was founded in 2021 and already is working with customers like Boeing, Penn Engineering, and Cummins. While First didn’t want to share the number of customers just yet, it’s clear some big players are interested in what his company is doing.
With almost 20 employees, the startup is hiring, especially engineers and employees with a specialty in machine learning. First says building a diverse workforce has been a priority from the start. "Even though we’re a small team," he explains, "we have dedicated full-time colleagues who are responsible for ensuring we’re building diverse candidate pipelines and hiring practices from day one."
A Diverse Team
Axion Ray’s commitment to diversity is evident in its partnership with Inspired Capital as their co-lead investor. "We were thrilled that we were able to partner with Inspired Capital," First says, "which is one of the largest female-led venture funds in the country."
The company’s diversity is not limited to its investors; its team also reflects this commitment. "We’re a small team," First notes, "but we have dedicated full-time colleagues who are responsible for ensuring we’re building diverse candidate pipelines and hiring practices from day one."
A Significant Investment
Today’s $7.5 million investment was co-led by Inspired Capital and Amplo, along with Boeing, Tinicum Venture Partners, and industry angels.
In a crowded field of startups vying for attention in the manufacturing sector, Axion Ray stands out with its innovative approach to tracking unstructured data and addressing the potential problems that come with it. With this significant investment, the company is poised to continue making waves in the industry and bringing about much-needed change.
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