Sold by: Coforge Limited
The AI ETL Script Converter accelerates the modernization of legacy Informatica ETL pipelines into scalable PySpark workloads for AWS-based data platforms. The solution automatically ingests Informatica XML exports, extracts detailed pipeline metadata, reconstructs transformation dependencies, and generates equivalent PySpark code using AI-driven reasoning powered by Amazon Bedrock. It produces accurate transformation logic, technical documentation, and end-to-end data lineage to ensure fidelity and transparency during migration. The platform runs on Amazon EKS and supports execution of generated PySpark pipelines on Amazon EMR, AWS Glue, and other Spark frameworks. This reduces manual migration effort, minimizes modernization risk, and enables enterprises to transition to cloud-native data engineering at scale.
Overview
Overview
The AI ETL Script Converter is a specialized modernization platform designed to help enterprises transition legacy Informatica ETL workloads into modern, cloud-native data engineering pipelines on AWS. By combining metadata extraction, AI-powered code generation and automated lineage reconstruction, the platform significantly reduces the complexity, cost, and risk involved in large-scale ETL modernization initiatives.
Core Capabilities
-
Automated Informatica-to-PySpark Conversion: The platform interprets Informatica XML exports—including mappings, transformations, connectors, workflow logic and schema definitions—and automatically generates equivalent, production-ready PySpark pipelines optimized for execution on AWS data processing engines.
-
Metadata Intelligence & Pipeline Modeling
The converter extracts granular metadata such as: -Transformation dependencies -Source and target schema structures -Workflow execution order -Mapping logic and connector relationships
This metadata is used to build a complete transformation dependency graph that mirrors the original Informatica logic with high fidelity.
-
AI-Powered Code Generation using Amazon Bedrock: Amazon Bedrock foundation models enable intelligent interpretation of complex ETL logic, automated transformation mapping, rule translation, and PySpark code generation. AI-driven reasoning reduces manual rewriting efforts and improves accuracy of transformation equivalence.
-
Automated Data Lineage & Documentation: The platform generates visual lineage diagrams and technical documentation covering:
-End-to-end pipeline flow -Transformation dependencies -Data movement from sources to targets
This ensures transparency, auditability and simplified engineering validation.
-
Pipeline Validation & Consistency Checks: Automated validation routines detect missing logic, schema mismatches, transformation inconsistencies or unsupported patterns, ensuring that generated pipelines are both accurate and production-ready.
-
Cloud-Native Deployment on AWS: The solution is deployable as a containerized application on Amazon EKS, providing enterprise-grade scalability and security. Generated PySpark pipelines can be executed on:
-Amazon EMR -AWS Glue -Any Spark-compatible processing environment
Business Benefits: -Accelerated modernization of legacy ETL workloads -Reduced migration risk via automated lineage, documentation and validation -Lower engineering effort through AI-generated pipeline logic -Future-ready PySpark pipelines optimized for AWS Big Data platforms -Improved observability with detailed lineage and dependency mapping
The AI ETL Script Converter enables a seamless, low-risk, and highly scalable path to modernizing ETL workloads for cloud-native architectures.
Highlights
- AI-powered Informatica-to-PySpark conversion using Amazon Bedrock for transformation logic interpretation and code generation.
- Automated metadata extraction and lineage generation, providing full pipeline visibility and technical documentation.
- Cloud-native deployment on Amazon EKS, with PySpark pipelines ready for execution on Amazon EMR or AWS Glue.
Details
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Pricing
Custom pricing options
Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.
Legal
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.