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How OpenEvidence uses Zilliz

< 10ms

Search latency with high recall

As published on zilliz.com. Captured by usedby on Oct 6, 2026.

What happened

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.

Summary written by usedby from the source page, in English. The figures are those of Zilliz and OpenEvidence, not ours.

  • 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.

From the page. zilliz.com, captured Oct 6, 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. Source, captured Oct 6, 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. Source, captured Oct 6, 2026

What the story claims, and what we checked

We compared the story with its live page on Oct 6, 2026.

  • The figure: < 10msCheckedThe figure is on the page; its label is our wording.
  • The passage quoted aboveCheckedCopied word for word from the page, near the name of OpenEvidence.
  • OpenEvidence uses ZillizCheckedConfirmed line. Latest check across sources: Oct 6, 2026.
  • The result itselfNot checkedWe quote it; we did not measure it.

Same company, same tool or same industry.

78%“78% lower latency, from over 700 milliseconds to 160 milliseconds end-to-end”OpenEvidence uses Baseten. Another tool at OpenEvidence~45 msP99 dense retrieval latency in production acrossConsensus uses Zilliz. Another customer of Zilliz<200msNeural search latency with Exa Instant, reducedExa uses Zilliz. Another customer of Zilliz