ModelOps: Managing AI at scale
One finalist is Modzy, a Vienna, Va., company that offers a ModelOps platform for deploying and managing AI at scale. The company aims to help customers generate value from their AI spending.
"Organizations are investing a lot in data science and analytics today, and not necessarily getting the return from the investment just yet," said Kirsten Lloyd, co-founder and head of go-to-market at Modzy. "Innovation stops in a lab."
Lloyd said she sees ModelOps as providing the same sort of rigor to AI models that DevOps brought to software development. Data scientists can tap Modzy's platform to more quickly integrate AI into enterprise applications, and then track, monitor and secure the models in production to ensure governance, she added.
From the CIO's point of view, Modzy offers centralized management of all the models within an enterprise, Lloyd said. That's an important consideration since data science organizations can be matrixed, with teams reporting to different leaders. As a result, CIOs might lack a sure grasp of AI developments across an organization.
"They can't necessarily track models being built and how they perform over time," Lloyd said.
A ModelOps platform, however, reduces risk while increasing visibility into projects, she said. Cost management is another plus. Centralized management encourages the sharing of AI models, avoiding redundancy and making better use of data scientists' time.
