{"slug":"independer-cuts-feature-delivery-50-with-lakebase","url":"https://findausecase.com/use-cases/independer-cuts-feature-delivery-50-with-lakebase","title":"Independer cuts feature delivery 50% with Lakebase","description":"Independer, the largest independent comparison platform in the Netherlands, used Databricks Lakebase to eliminate the export bottleneck between its Customer 360 data platform (built on Databricks and Unity Catalog) and the production APIs serving its website, customer service tools, and internal analytics. Because customer data had been fragmented across legacy on-premises systems, engineers previously had to write export scripts and load a separate SQL Server instance before building new features. By synchronizing gold tables directly with consuming services via Lakebase (built on PostgreSQL), Independer cut development work for new Customer 360 features by 50% and is now building GenAI agent proof-of-concepts that store state in Lakebase.","company":"Independer","industry":"Financial Services","country":"Netherlands","aiCapabilities":["Generative AI"],"technology":["Lakebase","Unity Catalog","Databricks Data + AI Platform","Microsoft Azure"],"deployment":"Public Cloud","problemStatement":"Its challenge was that customer data was fragmented across legacy on-premises systems and organizational silos, blocking the single customer view the business needed to deliver proactive, personalized experiences. You had to go shopping across the entire organization just to assemble a complete picture of a single customer. Every new feature hit the same wall. You couldn't touch the API until the export scripts were written, tested and loaded into a separate database.","solutionApproach":"Independer centralized its data inside Atlas, its internal data platform built on Databricks, pulling together data from across the business and processing it through layered jobs into a unified set of gold tables. With Lakebase, Independer eliminated its last-mile export bottleneck by synchronizing gold tables directly with the services that consume them, replacing fragmented export pipelines from data lake to production API.","businessValue":"With the export layer gone, Independer cut development work for new Customer 360 features by 50%. The team now iterates faster on the experiences powering the website, customer service tools and internal analytics. The GenAI team is actively building proof-of-concept agents that store state in Lakebase, with plans to move to production in the coming months.","evidence":{"band":"high"},"sourceUrl":"https://www.databricks.com/customers/independer/lakebase","dates":{"publishedAt":"2026-08-29T09:01:56.504Z","publishedAtSource":"pipeline","updatedAt":"2026-08-29T09:01:56.504Z"},"license":"Open for reading and citing with a link to https://findausecase.com/use-cases/independer-cuts-feature-delivery-50-with-lakebase. Bulk republication requires permission."}