Case Study: Zephyr Health achieves high-speed, scalable cloud analytics and unified data insights with Neo Technology's Neo4j

Cloud Analytics Platform Using Graph Database

Zephyr Health, a San Francisco–based company, built a cloud analytics platform that unifies diverse public and private healthcare data to surface connections—like the right physicians for clinical trials—that drive R&D and marketing decisions. The core challenge was combining disparate, frequently changing data sources into a single, user-friendly engine that lets nontechnical customers “be their own data scientist” while avoiding the performance and operational issues of their previous CLOB-based approach.

Zephyr implemented a new architecture using Neo4j for graph modeling and MongoDB for BI reporting, and layered a domain query language (Zquery) over both. A 12-week POC and rapid rollout produced a high-speed, scalable platform—handling 14–16 hop traversals in under 200 ms—enabling complex, customized queries in the cloud and supporting rapid growth and evolving business needs.

Zephyr Health Inc.