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How Hudl uses Encord

10x

“10x annotation speed improvement on tracking data”

As published on encord.com, April 2026. Captured by usedby on Oct 7, 2026.

What happened

Hudl's Applied Machine Learning team uses Encord as the central annotation and data management layer in its MLOps pipeline, annotating sports video and sensor data for model training. Hudl's own models pre-label the data, a validation agent flags errors, and annotators and data scientists work together in one workflow.

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

  • 40%“With the validation agent in place, the same process is now 40% faster.”

By integrating Hudl's own pre-labelling pipeline into Encord, use cases that previously required approximately 10 hours of manual annotation now take around 1 hour.

From the page. encord.com, captured Oct 7, 2026

Encord has broken down barriers between annotation and data science. Pre-labelling has probably been the biggest game changer for us. We've seen a 10x speed improvement on some of our most demanding projects.

Ben Irving, Senior Engineering Manager, Applied Machine Learning, Hudl. Source, captured Oct 7, 2026

What the story claims, and what we checked

We compared the story with its live page on Oct 7, 2026.

  • The figure: 10xCheckedPrinted word for word on the page, near the name of Hudl.
  • The passage quoted aboveCheckedCopied word for word from the page, near the name of Hudl.
  • The publication dateCheckedRead from the page’s own metadata, never guessed.
  • Hudl uses EncordCheckedConfirmed line. Latest check across sources: Oct 7, 2026.
  • The result itselfNot checkedWe quote it; we did not measure it.

Same company, same tool or same industry.

20-30%“Since implementing Encord, UVeye has seen around a 20-30% improvement in their data annotation rate”UVeye uses Encord. Another customer of Encord60%“Achieving reliable data pipelines for model training and evaluation 60% faster”Pickle Robot uses Encord. Another customer of Encord50%“The team estimates they are at least 50% faster compared to earlier stages of the project”Thoro.ai uses Encord. Another customer of Encord