Modernize legacy SAS platforms to accelerate innovation and bring down TCO

Infogain’s SAS to Databricks Migration Suite is a purpose-built GenAI automation framework that accelerates SAS to PySpark modernization using Databricks Lakehouse, Unity Catalog, and CI/CD orchestration. The suite leverages multi-agent orchestration, prompt intelligence, and automated validation to reduce migration effort by 50% and achieve 95%+ accuracy. 

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Accelerator Overview

Agentic


Orchestration


Framework

Coordinates multiple LLM-powered agents (Parser, Lineage, Converter, Validator) for fully automated SAS-to-PySpark migration.Built on Databricks Jobs with LangGraph-based agent routing and dependency control Feedback-driven prompt refinement for self-learning and accuracy improvement.

Benefit: 50% faster migration with 95%+ code accuracy and continuous model learning. 

Unity Catalog–


Integrated


Lineage


& Governance

Extracts SAS dataset dependencies and maps them directly to Unity Catalog entities. Block-level lineage and schema mapping to ensure referential integrity Unified metadata and access control across migrated workloads.

Benefit: Delivers full transparency, auditability, and compliance from source to Lakehouse. 

GenAI SAS to


PySpark


Conversion Engine

Transforms SAS logic to PySpark using rule-driven and LLM contextual translation. Prompt DB and Delta-based embedding store for reusable conversion intelligence Self-healing logic corrections via Code Quality and Auto-Fix agents.

Benefit: Generates production-ready, optimized PySpark with minimal manual rework. 

Validation & CI/CD


Automation

Automates testing, deployment, and validation pipelines natively on Databricks. Schema, row-count, and data-hash comparisons ensure output parity. Automated notebook deployment and rollback workflows via DevOps pipelines and Terraform.

Benefit: Ensures 100% validated, reproducible results across environments.

Agentic UI &


Feedback Loop

Interactive interface for reviewing conversions, lineage graphs, and quality metrics. Real-time user feedback captured for prompt optimization and error correction.  Power BI dashboards connected to Databricks SQL for visual tracking and reporting, using REST APIs.

Benefit: Enables collaborative governance and faster iterative improvement.