It’s widely understood that after machine learning models are deployed in production, the accuracy of the results can deteriorate over time. Arthur.ai launched in 2019 with the goal of helping companies monitor their models to ensure they stayed true to their goals. Since then, the company has also added explainability and bias mitigation to the array of services.
The tooling has been resonating in the market, and today the startup announced a hefty $42 million Series B. Company co-founder Adam Wenchel told TechCrunch it’s the largest round ever given to a machine learning monitoring startup.
Accuracy also means guarding against bias, and that’s something the company has been working on since we last spoke to them at the time of its $15 million Series A.
“We’ve worked a lot on the bias side of things. It’s becoming a lot more top of mind for people, like how do you keep these models from being discriminatory? And so we’ve done a lot of novel IP development around how do you automatically adjust the outputs of these models so that they meet whatever fairness constraints the customers want to achieve,” Wenchel said.
Explainability, as the name suggests, is understanding why you got the results you did. Wenchel uses the example of having high blood pressure, which could be from diet or other controllable factor, or it could be from a hereditary factor, you have no control over and might require medication to bring down. Understanding that there isn’t a one-size-fits-all answer is important can help prevent over generalizing what the machine learning model is telling you.
He said he definitely noticed a difference in raising this year versus the last time. “We had to meet with a dozen different investors to get those multiple term sheets as opposed to the frothy environment of 2020 when there were people who were calling every five minutes asking, are you ready? Are you ready? Are you ready yet? But it all worked out well for us,” he said.
Perhaps the company’s growth is one of the reasons for investor interest. The startup has averaged 58% ARR growth over the last four quarters, which looks even better when you consider the economic ups and downs we’ve been experiencing over the last couple of years.
The company has 55 employees today, up from 17 at the time of its Series A, and Wenchel says that diversity remains a company goal, one that they’ve been working on, both at the cap table level and at the employee level.
He says it’s particularly important in the research area, where having a diverse workforce can help prevent bias from creeping into their software. “We’ve published a number of papers and that team in particular is incredibly diverse, and I think a much better team for it,” he said.
Today’s round was led by Acrew Capital and Greycroft. The cap table includes Theresia Gouw from Acrew and Ashley Mayer from Coalition Operators. Gow will join the board under the terms of the funding.
Arthur.ai machine learning monitoring gathers steam with $42M investment by Ron Miller originally published on TechCrunch
