Build Enterprise Solutions For Model Operations & Governance

By Harish Doddi, CPO & Co-Founder

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In this episode of the Data Exchange, Ben Lorica speaks with Harish Doddi,
co-founder of Datatron, a startup focused on helping companies operationalize
machine learning. Over the past two years, Harish has worked closely with
enterprises to understand their needs in the areas of model operations and
model governance. Last year Harish and Ben, along with David Talby, wrote two
articles on these topics. In the first article, we described these emerging areas
(“What are model governance and model operations?”), and in the second we
listed lessons that ML engineers can draw from two highly regulated industries
(“Managing machine learning in the enterprise: Lessons from banking and health
. As machine learning becomes widely deployed, organizations will need to
develop processes and tools to ensure that models behave as intended. This
means having the right set of controls and validation steps in place.

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Hosted by Ben Lorica

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Topics Covered

  • MLOps, Model Governance, Model Observability.
  • How model governance is perceived and practiced in different industries.
  • Real-world examples of model governance, and organizational and staffing considerations that come into play.
  • CI/CD for machine learning.
  • Key enterprise features for model governance solutions.



Harish Doddi

CPO & Co-Founder

Over the past decade, Harish has focused on AI and data science. Before Datatron, he worked on the surge pricing model for Lyft, the backend for Snapchat Stories, the photo storage platform for Twitter, and designing and developing human workflow components for Oracle. Harish completed his master’s degree in computer science at Stanford, where he focused on systems and databases.