Ir al contenido principal
usedby
Herramientas, empresas

Cómo usa OpenEvidence Zilliz

< 10ms

Search latency with high recall

Tal como se publicó en zilliz.com. Capturado por usedby el 6 oct 2026.

Qué pasó

OpenEvidence runs an AI clinical decision tool that gives clinicians evidence-based answers from medical sources. It uses Zilliz Cloud as the vector search layer for retrieval, with a private, HIPAA-compliant data path.

Resumen escrito por usedby a partir de la página de origen, en inglés. Las cifras son de Zilliz y de OpenEvidence, no nuestras.

  • 4,000 QPS“The system supports roughly 4,000 QPS and serves more than 800,000 clinicians.”
  • 25 million“In March 2026 alone, OpenEvidence supported 25 million clinical consultations, and the number is still growing rapidly.”
  • 99%“With sophisticated quantization and refined strategy, Zilliz Cloud achieves 99% recall with an aggressively compressed index to serve high-QPS low-latency workload, unlike competitors that trade accuracy for speed.”

Zilliz Cloud consistently delivers sub-10ms latency with 99%+ recall. Each user query triggers multiple vector searches, yet responses return fast enough that the latency is not visible to clinicians.

De la página. zilliz.com, capturada el 6 oct 2026

Zilliz Cloud has helped us create a strong foundation behind the scenes as we continue to grow and serve hundreds of thousands of clinicians.

Jagath Kumar, Head of Performance Engineering, OpenEvidence. Fuente, capturada el 6 oct 2026

We believe AI is becoming a meaningful support layer for physicians, but the experience has to feel trustworthy, reliable, and seamless. Building that kind of product requires a strong foundation behind the scenes. Zilliz Cloud has helped us create that foundation as we continue to grow and serve hundreds of thousands of clinicians.

Jagath Kumar, Head of Performance Engineering at OpenEvidence, OpenEvidence. Fuente, capturada el 6 oct 2026

Lo que dice la historia, y lo que verificamos

Comparamos la historia con su página en línea el 6 oct 2026.

  • La cifra: < 10msVerificadoLa cifra está en la página; su etiqueta es redacción nuestra.
  • El pasaje citado arribaVerificadoCopiado palabra por palabra de la página, cerca del nombre de OpenEvidence.
  • OpenEvidence usa ZillizVerificadoLínea de nivel Confirmado. Última verificación entre todas las fuentes: 6 oct 2026.
  • El resultado en síNo verificadoLo citamos; no lo medimos.

Misma empresa, misma herramienta o mismo sector.

78%“78% lower latency, from over 700 milliseconds to 160 milliseconds end-to-end”OpenEvidence usa Baseten. Otra herramienta en OpenEvidence~45 msP99 dense retrieval latency in production acrossConsensus usa Zilliz. Otro cliente de Zilliz<200msNeural search latency with Exa Instant, reducedExa usa Zilliz. Otro cliente de Zilliz