Gjensidige breaks down data silos and speeds AI model deployment with Databricks
Gjensidige migrated to the Databricks Data + AI Platform to unify data engineers, scientists and analysts on one tech stack, rebuilding a single-person-dependent commercial renewal rules engine and cutting AI model development and deployment time from days or weeks to a few hours.
Overview
Gjensidige migrated to the Databricks Data + AI Platform to unify data engineers, scientists and analysts on one tech stack, rebuilding a single-person-dependent commercial renewal rules engine and cutting AI model development and deployment time from days or weeks to a few hours.
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Inspect the highlighted sourceThe challenge
Gjensidige's data infrastructure was fragmented and overly reliant on legacy, on-premises systems, with a fragmented analytics solution that made it hard for teams to know what others were working on, and a critical commercial renewal process relied on complex scripts managed by a single individual, risking loss of access to a vital business function if that person left.
The solution
Gjensidige migrated to the Databricks Data + AI Platform, unifying data engineers, scientists and analysts on the same tech stack, rebuilding the commercial renewal rules engine with a modern architecture that a broader team could maintain, and implementing generative AI applications including retrieval-augmented generation (RAG) for real-time marketing actions.
Reported business value
With Databricks, Gjensidige has reduced the time it takes to develop and deploy AI models from days or weeks to just a few hours, broken down data silos across the company, and improved its ability to share and reuse data products across teams, enhancing cross-selling and customer engagement.
Sources
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This record was researched and written with AI assistance, and its claims were checked against the sources above. (EU AI Act art. 50 transparency notice.)
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