Case Study: Lippert achieves faster customer support innovation and millions in savings with Databricks

Improving customer support for the road ahead

Lippert, a $3.8 billion global manufacturer serving RV, marine, and automotive brands, was struggling as call volumes surged into the millions and legacy tools like Synapse and Dynamics 365 could not keep up. Fragmented systems, slow onboarding, and limited visibility into service quality left the customer support team reactive and stretched thin. Databricks and Mosaic AI helped Lippert modernize its data and support operations with a scalable lakehouse and AI-driven workflow.

With Databricks, Lippert built and deployed customer support agents to automate call and case summarization, improve question-answering accuracy, and monitor performance in real time. Using synthetic data and Mosaic AI evaluation tools, Lippert improved model accuracy from 33% to 56% before SME review, and the company reports AI agents that can save an estimated $2.1 million and 106,000 hours. Databricks also enabled faster insights, stronger governance, and a repeatable path to production for future agents across the business.

Lippert

Kenan Colson

VP of Data and Artificial Intelligence