Automated Translation of Legacy ETL Configurations.
We build focused software to translate legacy Informatica PowerCenter XML repositories into modern, testable Snowflake SQL and dbt configurations. By applying structured, deterministic translation logic to help streamline migration, we help teams navigate their migration path while keeping control in the hands of data engineers.
The Operational Redo Cost of ETL Migrations
Legacy ETL environments like Informatica PowerCenter often see critical business logic embedded in complex legacy repositories. Traditional migration efforts rely heavily on manual rewrites—a slow, labor-intensive process highly prone to translation errors. Furthermore, checking that target cloud schemas run like the legacy source mappings is difficult, traditionally requiring extensive manual record-by-record comparison and data reconciliation.
Predictable Engineering and Explainable Architecture
Data migrations require strict predictability. Our hybrid engineering approach focuses on separating deterministic rules from supportive artificial intelligence, providing transparent and reviewable migration logic.
Deterministic Core
Rule-based, testable algorithms handle structured tasks like parsing XML schemas and mapping execution flows. This deterministic engine ensures that core translation patterns produce consistent, reproducible SQL configurations.
Complementary AI
We deploy artificial intelligence strictly as a targeted, supportive layer to translate complex custom expressions, suggest remediation paths, and explain code transitions in natural language.
The XML to dbt Translation Pathway
We represent our translation process as a structured, visible progression. Your legacy XML definitions pass through dedicated conceptual processing areas to emerge as modern, organized dbt and SQL models, complete with a transparent validation overview.
Targeted Operational Workflows
Source Parser & Ingest Concept
Designed to ingest legacy Informatica XML configurations, mappings, and connection definitions to establish a clean source baseline.
Dependency Graph Mapping Concept
Focuses on parsing internal data flows to construct a logical representation of sources, targets, and intermediate transformation rules.
Target Code Generator Concept
Translates validated source mappings into clean Snowflake SQL and structured dbt configurations.
Behavioral Validation Concept
Aimed at comparing source and target outputs, helping data engineers verify record counts and structural data consistency.
Transparent Migration Reporting Concept
Designed to produce a comprehensive report highlighting automated translations, unmappable components, warnings, and elements requiring manual engineering review.
Transparent Migration Logic
Automation is only as good as its transparency. Our interface is designed to maintain architectural visibility and review, keeping human operators in control. Instead of guessing or forcing unverified configurations, the system highlights unmappable legacy patterns and reports warnings clearly. This provides visibility into generated configurations so database architects can review, edit, and verify outputs before deployment.
Strategic Beta
Our Legacy Data Modernization utility is currently in its Strategic Beta phase. We are actively executing internal technical gap analyses, accuracy benchmarking, and validation against legacy setups. We focus on refining the utility's core logic.
Modernize with Visibility
Discuss your modernization challenges with our team. We partner with enterprise database leads and data teams seeking a transparent, structured process to transition their configurations.