DataForge AI assesses your legacy SSIS, Informatica, or Talend estate; uses generative AI to accelerate migration to Azure Data Factory, Microsoft Fabric, or Synapse; and lands you on a medallion architecture with DataOps baked in.
Where DataForge AI fits — when modernizing data pipelines onto Azure without burning a year on a rewrite.
SSIS packages running on Windows servers nobody patches. Informatica jobs documented in Word files from 2017. Brittle Python scripts that broke last month and nobody knows why. Every new data source is a project. Every change request is a ticket. The data team spends 70% of its time on maintenance and 30% on actual value creation.
DataForge AI doesn't just migrate the pipelines — it re-architects them. Generative AI accelerates the conversion of legacy ETL logic to modern Azure Data Factory, Fabric Data Pipelines, or Synapse. The landing architecture is medallion (bronze/silver/gold) on Azure Data Lake. Real-time + batch run on one platform. Data quality, lineage, and observability are built in, not bolted on. Git-based version control and CI/CD come standard.
Layered design, production tooling, native Azure integration. Every component is one we use in shipping client systems — not a theoretical reference stack.
Outcome ranges are illustrative — based on structural economics of the problem and what comparable production systems achieve. Actual results depend on baseline maturity, data quality, and integration depth.
Our products are designed to compose. DataForge AI works standalone, but most enterprise engagements combine three or four — built on a shared data foundation and a single Azure tenant.
Tell us about your current setup and the outcome you'd want from DataForge AI. We'll come back within one business day with a path forward.