Case Study: OpenEvidence achieves sub-10ms, high-recall medical AI search with Zilliz Cloud

OpenEvidence delivers 99%+ recall and sub-10ms search with Zilliz

OpenEvidence, an AI-powered clinical decision tool used by over 800,000 clinicians, faced significant challenges scaling its platform to deliver reliable, low-latency medical information. Their existing vector search system could not consistently meet the sub-10ms latency required for real-time physician use, struggled with peak traffic of thousands of queries per second, and had difficulty maintaining high search recall while ensuring HIPAA compliance. To support millions of monthly consultations without compromising patient safety, OpenEvidence needed a more robust solution and turned to Zilliz Cloud.

By implementing Zilliz Cloud, a fully managed vector database, OpenEvidence achieved its critical performance goals. The Zilliz Cloud solution delivers consistent sub-10ms search latency with over 99% recall, easily handles 4,000 queries per second, and provides a HIPAA-compliant infrastructure. This has enabled OpenEvidence to reliably scale its service to hundreds of thousands of clinicians, supporting 25 million consultations per month while significantly reducing the operational overhead on its engineering team.

OpenEvidence