Case Study: Wejo achieves 50x faster time-to-insight for connected-car analytics with Databricks

Enabling the connected car with AI

wejo is a connected‑car company that has curated over 140 billion miles of driving data and ingests more than 15 billion data points daily from OEMs and navigation systems across millions of vehicles. Faced with disjointed streaming sources, rigid MapReduce clusters, and the need to process over three trillion monthly data points (delivering car-to-marketplace insights in under 40 seconds), wejo struggled with slow, resource‑intensive pipelines and long job runtimes that hindered innovation.

By adopting Databricks’ unified analytics platform with managed cloud clusters, multi‑language support and native Delta Lake, wejo consolidated batch and streaming ETL, accelerated ML development, and improved collaboration. The result: dramatically faster, cheaper large‑scale processing and ML—about 20x faster data processing, 50x faster time‑to‑insight, and a 90% reduction in time‑to‑market—enabling hours‑not‑weeks delivery of new automotive innovations.

Wejo

Steve Pimblett

Chief Information Officer and Data Officer