For scaling enterprise MLOps, Domino delivers.
Configuring compute resources. Onboarding new data scientists. Building, validating, deploying, and monitoring new models. It’s complicated. And every piece of the MLOps lifecycle has a cost.
Forrester conducted an in-depth study to measure these costs against the value Domino’s enterprise customers realize for their business. Here’s a look at what they found.
Free up 200 hours for every data scientist to do more actual data science.
Shared environments and tools make teams using Domino far more efficient, to the tune of $5 million in added value. More collaboration → model velocity acceleration.