Machine learning is meant to make our lives easier because its allows computers to perform specific tasks without explicit instructions from humans. However, achieving it successfully is complicated. Once the model is developed and tested in a lab, there isn’t a mechanism in place to monitor how well its doing later on.
So, CEO and co-founder, Adam Wenchel, created Arthur to track the performance of machine learning models in the real world.
“We are an AI monitoring and explainability company, which means when you put your models in production, we let you monitor them to know that they’re not going off the rails, that you can explain what they’re doing, that they’re not performing badly and are not being totally biased — all of the ways models can go wrong,” Wenchel told Tech Crunch.
The Arthur platform is described as a “single pane of glass for your AI applications,” on its website. It flags unwanted problems and biases, identifies opportunities to increase performance and explains why it is making certain assessments.
The funding round, which closed in August, was co-led by Work Bench and Index Ventures. Hunter Walk at Homebrew, Jerry Yang at AME Ventures and others also participated.
The NYC-based company currently has 10 employees and is accepting a limited number of innovation platforms to work with the Arthur AI platform.