Case Study: Theator achieves AI workflow automation and major cost savings with ClearML

AI Workflow Automation with - and for - Surgical Precision

Theator, a surgical intelligence company using computer vision and machine learning, needed a way to manage heavy AI experimentation without buying expensive GPU hardware or dedicating DevOps staff to server management. As their workloads grew, they wanted better visibility, scalability, and control over cloud costs while keeping development focused on improving surgical outcomes.

ClearML provided its automation and orchestration module, along with ClearML Agent, and Theator integrated it into their environment in less than a week. ClearML automatically spun machines up and down based on demand, tracked GPU, CPU, RAM, VRAM, and network usage, and made experiments easier to reproduce. Theator reported immediate AWS savings, eliminated the need for a dedicated DevOps engineer, and estimated direct ML-Ops cost savings of about $130K-$170K annually, with additional productivity gains from faster, hands-free experimentation.

Theator

Dotan Asselmann

Co-founder and CTO