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The bottleneck in AI has shifted downstream. Data structure, access, and orchestration across complex environments now determine what can scale.
As AI systems expand in scope and complexity, gaps in data flow, inconsistent access patterns, and brittle pipeline design are becoming critical failure points. These issues surface most clearly under production workloads, where latency, reliability, and context continuity are non-negotiable.
This roundtable webinar explores how technical leaders are addressing these constraints by engineering a scalable foundation built to support modern AI workloads in production environments.
You'll Learn How To:
- Spot where AI systems break at scale in data flow, access, and latency
- Understand why traditional pipelines fail for generative and agentic systems
- Define what production AI architectures require
- Improve orchestration and reliability at the system level
Register Now to attend the webinar Building AI's Data Core: Architecting Scalable Data Foundations for AI. Don't miss this live event on Thursday, October 8, 11 AM PT / 2 PM ET.
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MODERATOR |
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Amar Srivastava
Community of Practice Director
Informatica from Salesforce |
Vikram Kulkarni
Area Vice President
Perforce Delphix |
Ebrahim Alareqi
Principal Machine Learning Engineer
incorta |
Steve Richardson
Senior Cloud Solutions Architect
NetApp Instaclustr |
Stephen Faig
Research Director,
Unisphere Research and DBTA |
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