Case Study: Quby scales to 400,000+ households and accelerates ML-driven smart-home services with Databricks Unified Data Analytics Platform on AWS

Quby Scales to Hundreds of Thousands of Users by Using a Unified Data Analytics Platform on AWS

Quby, the developer of the Toon connected‑home platform, collects petabytes of energy-usage data from over 400,000 households across Europe to power smarter home energy and comfort services. The company wanted an AI-first approach to use ML on streaming IoT data but was held back by on-premises Hadoop clusters that couldn’t scale cost‑effectively, caused unreliable streaming processing, and led to siloed data science workflows.

Quby migrated its infrastructure to Databricks on AWS, using Databricks Workspace, Delta Lake and MLflow to centralize analytics, automate cluster management, and standardize ML development. The move enabled scalable, distributed ML and faster collaboration—cutting POC-to-product cycles dramatically, accelerating releases to production, and allowing Quby to deliver more personalized, data‑driven services while shifting from a hardware to a service‑oriented business model.

Quby

Stephen Galsworthy

Chief Data Officer