Deepchecks Secures $14 Million Funding to Continuously Validate Machine Learning Models

Deepchecks, a continuous machine learning validation startup, has launched its platform for public use following a $14 million seed funding round. The investment was led by Alpha Wave and included participation from Hetz Ventures and Grove Ventures. Deepchecks was founded by CEO Philip Tannor and CTO Shir Chorev, who originally set out to create a machine learning operations platform but realized a larger opportunity lay in validating the models. The platform helps MLOps teams gain visibility into their machine learning models, from development to deployment to operation and production. The goal is to ensure that high-quality machine learning models receive regular updates through testing and validation at every stage of their lifecycle.