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Overview
Legacy Statistical Analysis System (SAS) is expensive, rigid, and difficult to modernize for today’s cloud-native enterprise environments. This whitepaper shows a structured, multi-agent AI approach that translates SAS into PySpark (an open-source, distributed processing framework built on Apache Spark) while preserving critical business logic (such as domain-specific rules, data transformations, and reporting workflows) and reducing the risk of errors, delays, and cost overruns during migration.
You’ll learn why manual rewrites stall, how automated parsing-translation-validation works, and where it delivers faster time-to-cloud adoption. Built on LTIMindtree’s Scintilla.AI principles, this whitepaper offers a practical blueprint for CIOs, CTOs, and data leaders planning SAS decommissioning or cloud migration.
What’s Inside the Whitepaper
Why SAS is unsustainable in cloud-first strategies
Where manual rewrites fail
How a multi-agent AI system automates SAS-to-PySpark
What enterprises gain
Introducing Scintilla.AI
Download the Whitepaper
Discover how an AI-driven approach simplifies SAS modernization and delivers business outcomes such as cost efficiency, faster cloud adoption, and the ability to unlock scalable, cloud-native analytics that fuel growth, innovation, and competitive advantage.
