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Deploying agentic AI on legacy infrastructure is like attempting to power a self-driving car with a steam engine. While autonomous agents require low-latency, headless data delivery and semantic consistency for real-time inference, legacy architectures remain tethered to batch-oriented, monolithic processing. These fragmented environments lack the metadata-driven agility and elastic scale necessary to feed the next generation of AI-driven pilots.
In this session, we’ll discuss why cloud modernization is critical to operationalizing AI. You’ll leave with a technical blueprint for consolidating fragmented legacy workflows into a unified, cloud-native environment, helping you move beyond technical debt to build a high-throughput, AI-powered data foundation.
Join us for an interactive conversation on:
The readiness gap: Identifying the architectural bottlenecks in legacy stacks that impede agentic AI throughput and model accuracy
The modernization lifeline: Identifying critical-path transformations that require immediate modernization versus stable on-premises technical debt
Making the move easy: Removing the friction and risk from legacy-to-cloud migrations through automation and modernization programs
Unified excellence: Consolidating disparate data services, including integration, quality, and governance, under one architectural umbrella to support autonomous agents
Presenters:
Aashoo Saxena
VP of Product Management, Salesforce
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