Case Study: J.B. Hunt achieves 99.8% faster freight recommendations and $2.7M in IT savings with Databricks

Driving freight transportation into the future

J.B. Hunt, a leading North American transportation and logistics provider, faced fragmented carrier data, legacy enterprise data warehouses, and rapidly growing telemetry from trucks that prevented real-time analytics, scalable ML and secure self-service. Those limitations made dynamic freight matching, tracking and predictive modeling slow or impractical across the business.

J.B. Hunt rebuilt its data platform with Databricks Lakehouse on Google Cloud (Delta Lake, MLflow) and Immuta for automated governance, enabling real-time streaming, reusable ML workflows and fine‑grained security. The platform delivered faster freight recommendations (99.8% improvement), the ability to train thousands of models in under four hours, and about $2.7M in IT infrastructure savings while supporting new capabilities like predicted ETAs and secure self‑service analytics.

J.B. Hunt

Joe Spinelle

Director, Engineering & Technology