Our mission is to build trustworthy and responsible AI.
If you’re a data scientist like us, you probably build a lot of ML models but have a hard time explaining how your models work. Your business managers and clients are unimpressed by your technical metrics and have a hard time trusting your models. Heck! Even you don’t fully understand how your model behaves. Even worse, you still deploy your models in production without monitoring their performance and behavior. It’s like flying blind!
You get the idea. Why is that? Let’s be honest: model explainability and performance monitoring are problems that we face frequently. The tools we use are not helpful and demand a lot of technical customization to make them compatible with our models and environments. The enterprise solutions are expensive, require us to go through a lengthy decision-making process and take a lot of time to implement.
Our job, as data scientists, is to explore data, build trustworthy and fair models, and ensure the models we deploy in production generate the value we are hired to create. But it’s tough to do while building complex models, handling engineering problems and negotiating our way into implementing enterprise solutions.
We need tools that are both powerful, affordable and quick to use. Tools that make our work more effective and ensure our AI models are successful in production. Tools that fulfill our needs when we’re small and scale as our team grows.
That’s why we’re building explainX.
Born in the midst of COVID-19, we are a 100% work from home company.
We'd love to hear from you.
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