Recalls are costly and damaging to any company, regardless of size or market.
For example, McKinsey estimates that recalls for companies that manufacture medical devices have cost $600 million in recent decades. The reputational impact tends to be long-lasting. Customers won't forgive you right away. According to a Harris Interactive poll, 55% of buyers said they would change brands after a recall, and 21% said they would avoid buying brands made by the manufacturer of the recalled product.
So what should a business do? Well, perhaps you should look to AI, suggests Daniel Furst.
The first is the CEO of Axion Ray. The company is developing an AI-powered platform that predicts product failure by ingesting signals from field service reports to sensor readings and correlating those signals with geolocation and other data. .
It's big business.
Axion Ray, valued at $100 million, today announced that it has raised $17.5 million in a Series A round led by Bessemer Venture Partners with participation from RTX Ventures, Amplo, and Inspired Capital. The new tranche brings New Castle, Delaware-based Axion's total funding to $25 million, which First says will be used to expand the platform's capabilities, enter new industries and grow Axion's workforce. It is said that it will be allocated.
The idea for Axion came to Furst while he was working in McKinsey's AI strategy division, he says. He found that projects that leveraged AI to prevent product issues often failed because the AI wasn't fine-tuned enough.
“To be successful, AI solutions that proactively mitigate problems must be layered within the product and have workflows that different groups can use to collaborate and solve problems. It is enabled by a precision, scalable AI platform,” said Furst. “No it [the right solution], different groups across the enterprise perform siled analysis of emerging quality issues. This creates duplication and lack of collaboration. ”
We launched Axion Ray for the first time in 2021 to not only provide a way to detect warning signs that a product may be failing, but also to help different teams within an organization (engineering, program, product, production, , field quality, and customer support). The problem and its associated data.
“Product quality issues can impact end users in the following cases: [the] The issue is not being addressed quickly and efficiently,” Furst said in an interview with TechCrunch. “Manufacturers struggle to proactively manage emerging issues impacting their customers. Field quality teams are forced to manually sift through cumbersome data sources to understand potential new issues. Because we spend a huge amount of time analyzing it.”
That's where Axion Ray can help, Furst said.
He cites the example of anti-lock braking systems failing in certain car models. Axion Ray's algorithms first detect problems in service field reports and then potentially identify the same or similar problems across call center complaints, reports from car dealership visits, and car telemetry measurements. .
“We use specialized AI to scan messy, unstructured, and disconnected data across various systems and alert us to recurring product quality issues,” Furst explained. . “We can help manufacturers understand, for example, that updating camera hardware and software causes a spike in specific error codes, telematics anomalies, call center calls, and parts returns. .”
First would argue that this is because the amount of data that Axion ingests is huge, and for good reason. But how does Axion handle this from a privacy perspective?
Axion says it typically retains data “for the duration of an active account,” or as stated in a customer's contractual agreement. Product owners concerned about data retention may be concerned about this vague policy. However, Axion initially claimed that he would delete customer data within 30 days of receiving the request.
“We are committed to handling customer data responsibly,” he added.
With a team of 70 employees and customers in healthcare, consumer electronics, aviation, automotive and industrial equipment including Boeing and Denso, Furst said he is confident in Axion's growth trajectory.
“There are multiple trends that have supported Axion Ray's expansion,” Furst said. “Many industries are releasing new technologies that are creating unforeseen problems, such as electric vehicles and other software-rich products. Manufacturers are also partnering with new suppliers they have never worked with before. As a result, more quality issues are occurring than ever before.Finally, manufacturers want to benefit from AI, which improves the skills of their employees and helps automate more manual tasks. I am.”
Kent Bennett of Bessemer Venture Partners added in an email: The excitement we hear from our customers about Axion speaks to the company's clear impact. The ROI his AI command center delivers by increasing uptime, customer satisfaction, and reducing costs has been a catalyst for significant growth in his customer base. ”