From bottleneck to strategic asset: the data scale-up of one of Brazil’s largest payment companies

Modernizing the data foundation of a company that processes roughly 8% of Brazil’s GDP takes more than swapping technology: it means doing it without stopping operations for a single day. That was the challenge faced by one of Brazil’s largest digital transaction companies, and the origin of this Digiage case study in Data Modernization and Artificial Intelligence with Databricks.

The legacy environment had reached its limit. Multiple analytics platforms ran in parallel, many routines were undocumented and conflicting sources produced different numbers for different areas of the same company. Without trust in the foundation, mission-critical AI use cases, such as risk and fraud intelligence, were out of reach.

Together with Digiage, the company rebuilt its data foundation on the Databricks Lakehouse, with Delta Lake, Unity Catalog and Databricks SQL Serverless. The migration was carried out through controlled coexistence, with the legacy and new platforms running side by side. The result: more than 4,500 tables modernized, more than 2,700 processes migrated to production with full stability, 1,393 obsolete processes retired and zero days of operational downtime.

The project was structured in four stages: the foundation, with the new architecture and governance standards; controlled coexistence between the legacy and new environments; enterprise-wide adoption by the teams; and value creation, with analytics, conversational data access and AI agents embedded in business workflows. Today, the same foundation powers three capabilities in production: advanced analytics, natural-language data queries and governed AI agents — including agents that negotiate with customers over WhatsApp under human supervision.

This case study shows, in practice, how governance, methodology and large-scale data engineering turn data into a strategic asset and pave the way for AI that scales securely.