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How Zoominfo uses Pinecone

>50%

“>50% increase in user engagement, driven by more relevant and timely recommendations”

As published on pinecone.io. Captured by usedby on Oct 3, 2026.

What happened

ZoomInfo's Applied AI team uses Pinecone as the vector database behind a real-time contact recommendation system. It runs semantic search over hundreds of millions of contact embeddings so users get personalized contact suggestions as soon as they view a company profile.

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

Pinecone enabled us to build, scale, and optimize a real-time contact recommendation system that processes thousands of large-embedding-model vector search queries per second, which has driven a 2x improvement in relevancy and 50% boost to user engagement.

From the page. pinecone.io, captured Oct 3, 2026

Pinecone enabled us to build, scale, and optimize a real-time contact recommendation system that processes thousands of large-embedding-model vector search queries per second, which has driven a 2x improvement in relevancy and 50% boost to user engagement.

Tamiro Scholer, Senior Data Scientist at ZoomInfo, Zoominfo. Source, captured Oct 3, 2026

What the story claims, and what we checked

We compared the story with its live page on Oct 3, 2026.

  • The figure: >50%CheckedPrinted word for word on the page, near the name of Zoominfo.
  • The passage quoted aboveCheckedCopied word for word from the page, near the name of Zoominfo.
  • Zoominfo uses PineconeCheckedConfirmed line. Latest check across sources: Oct 3, 2026.
  • The result itselfNot checkedWe quote it; we did not measure it.

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