More AI tools usually means more questions: who’s using what, what’s it costing, and is it actually working well?
In this webinar, Matei Zaharia and Kasey Uhlenhuth show how Unity Gateway helps teams see and control AI usage across models, agents, harnesses, and workflows.
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We found and eliminated an estimated $1.2M a year in wasted AI spend and lost productivity in one hour.
Here's how 👇
Using Unity Gateway tracing and Genie One, we identified seven small MCP-server bugs that were quietly driving:
• ~$499K/year in wasted tokens
• ~12,000
Here's how to run Jev-style decision models directly on governed data with Databricks 👇
Serve open-weight models like SemIf-OpenJev on serverless GPUs with AI Runtime + Model Serving, then call them directly from SQL or Lakeflow jobs using ai_query to return structured
A new model comes out roughly every five days. The best model for a coding task today may not be the best or most cost-effective choice a few months from now.
The new Unity Gateway CLI helps organizations keep up with that pace.
Developers can keep working in Claude Code,