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DataRemodeler
Legacy data modernisation designed for audit, access, and trust.
About DataRemodeler
Data Remodeler is a legacy data modernisation platform that makes it safe to retire old systems without losing access to the data, meaning, or trust inside them. Data Remodeler functions as a legacy data modernizer, turning ageing systems into modern, trusted data assets and enabling organisations to finally switch the old platforms off. Most legacy platforms persist not because they are good systems, but because the data they contain is still operationally, legally, or clinically essential. The risk of losing historical meaning prevents organizations from modernizing. Data Remodeler removes that risk. We specialize in understanding legacy data before modernization. Our platform analyses schemas, SQL, reports, and real-world usage to build deep, machine-readable system understanding. From that foundation, we modernize legacy data into reporting-ready models that preserve historical meaning, lineage, and compliance, allowing legacy platforms to be safely decommissioned. What we enable Safe, defensible legacy system modernization Faster time-to-decommission with reduced programme risk Preservation of clinical, financial, and operational meaning Continued audit, research, and reporting access on modern platforms Proven NHS modernization at scale Our modernization approach has been production-proven within the NHS, including: ~£6.5m in annual savings 15+ legacy systems modernized and decommissioned 60+ source systems consolidated Long-term archive delivered in ~90 days Why our approach is different Traditional migration and ETL tools assume legacy systems are already understood. In practice, that understanding has often been lost. Data Remodeler is modernization-first through understanding—combining automation with engineer-in-the-loop validation to deliver modernization programmes leadership can trust. Industry: Digital Health · Data Modernization · Legacy Transformation Focus: NHS, public sector, regulated enterprises
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