The pressure on enterprise data leaders has rarely been sharper. Boards want AI initiatives delivered. Regulators want proof of data integrity. Business units want analytics they can defend. All three demands share one dependency: data that is not just modernized, but demonstrably trustworthy. Closing that gap – between data that has been transformed and data that can be proven accurate – is what this partnership is built to do.
Vega IT is an AI-native engineering company with more than 1,000 enterprise programs delivered, specializing in complex data transformation and modernization at scale. Vega IT architects and builds platforms where data must be trustworthy; Datagaps provides the Gartner-recognized capability to certify that trustworthiness.
“Data transformation is a major enterprise investment, and its return depends on whether the data it produces can be trusted,” said Narendar Yalamanchilli, Founder & CEO of Datagaps. “Together with Vega IT, we reduce validation cycles by 70%, achieve 100% data coverage without sampling, and give CDOs and CIOs an evidence-based answer to the two questions that determine transformation success: are we AI-ready, and are we audit-ready?”
Rather than treating data quality as a downstream fix, the partnership embeds assurance into every stage of the transformation itself – compressing risk, time, and cost by closing the gap between building a modern data environment and proving it performs as required.
Reduction in the data validation cycle
Pipeline coverage — no sampling, every record
Time saved on manual testing across migration & BI
“Innovation can only happen when companies trust the data behind their decisions,” said Stanislav Grujic, Co-CTO & Executive Partner at Vega IT. “By combining our engineering excellence with Datagaps’ automated data assurance, we help organizations transform with greater speed, accuracy, and confidence.”
The partnership is designed for CDOs, CIOs, and technology executives in financial services, insurance, and healthcare, where data accuracy is a regulatory requirement, not just a goal. By aligning transformation and validation from the outset, it gives executives a defensible, evidence-backed answer at sign-off – not one reconciled after the fact.
