PRT108-SFoundationalLightning talkPartner Showcase Playbook 4 live updates

From Experiment to Production: Unlock AI Deployment Bottlenecks

What this session is about

How fast can AI drive results Banks seek competitive advantage while staying compliant, and the public sector aims to enhance citizen services and boost productivity. In this session, we demonstrate how Synthetic Data and robust AI Governance operationalise AI with confidence. Learn how SAS Viya on AWS enables effective deployment, unlocking faster, better decisions through a proven AI framework.

Playbook

Editorial commentary · what to actually do about this on Monday

The concept
Synthetic data + AI governance for compliant AI deployment. Banking and public sector focus.
Why it matters
Data scarcity and privacy regulations make synthetic data essential for some use cases — particularly testing and edge-case coverage.
The hard parts
Synthetic data quality varies. Bad synthetic data poisons models in subtle, hard-to-detect ways.
Playbook moves
(1) Validate synthetic data against real holdouts. (2) Don't trust unvalidated synthetic data, especially for training. (3) Document the generation process for audit.
The surprise
Synthetic data is most valuable not for training but for *testing*. Edge cases that don't occur in real data can be synthesised to stress-test models. That's the underrated use case — and it solves problems training-set augmentation doesn't. ---

Independent editorial perspective — not an official AWS or speaker statement. Designed for executives evaluating what to brief their teams on next.

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