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How Handshake uses Arize AI

15+

“The approach enabled 15+ production use cases in the first six months”

As published on arize.com. Captured by usedby on Oct 5, 2026.

What happened

Handshake routes its LLM-powered product features through an internal orchestration service that traces every call to Arize AX. The team uses those traces and golden datasets for evals, LLM-as-a-judge, cost breakdowns and production monitoring.

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

  • one to two weeks“with a typical path from idea to live measured in one to two weeks and major bugs fixed early.”

The approach enabled 15+ production use cases in the first six months, with a typical path from idea to live measured in one to two weeks and major bugs fixed early.

From the page. arize.com, captured Oct 5, 2026

The ability to run real-time online evaluations has been crucial as we've developed our agents.

Ralph Bird, Principal Engineer, Handshake. Source, captured Oct 2, 2026

Arize AX is where all of the traces go—it’s been fantastic to collect everything in one place for evals and iteration.

Kyle Gallatin, Technical Lead Manager of ML Infrastructure, Handshake. Source, captured Oct 2, 2026

What the story claims, and what we checked

We compared the story with its live page on Oct 5, 2026.

  • The figure: 15+CheckedPrinted word for word on the page, near the name of Handshake.
  • The passage quoted aboveCheckedCopied word for word from the page, near the name of Handshake.
  • Handshake uses Arize AICheckedConfirmed line. Latest check across sources: Oct 5, 2026.
  • The result itselfNot checkedWe quote it; we did not measure it.

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