Your execs want more AI projects, and your software engineers can now ship AI-generated code in a single prompt. Your data engineering team still owns data quality. How do you keep up and maintain quality without becoming the bottleneck? You start by looking at the strategies you use to define the contract between the data platform and the agents on top of it.
In this webinar, we'll show how our enterprise customers have put orchestration first to establish a variety of AI initiatives at scale, including revenue-driving AI products and internal AI tooling that enables self-service data access across the organization.
You'll learn why data orchestration is the critical piece to:
- Improve data quality with automatic, agent-driven DQ tests on unstructured data
- Supply your customer-facing AI applications with fresh indexes of changing data
- Modernize your data context to service both human and agentic users across the organization
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