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How Captur uses Weights & Biases

As published on wandb.ai, January 2025. Captured by usedby on Oct 8, 2026.

What happened

Captur's ML team uses Weights & Biases to track training runs and metrics, record datasets, training, evaluation and deployment as Artifacts, and manage release candidates and production deployments through Registry for its on-device computer vision models.

Summary written by usedby from the source page, in English. The figures are those of Weights & Biases and Captur, not ours.

W&B has become a critical component for Captur, not just in terms of serving as the system of record for all ML results and activities, but also with Registry becoming the hub for all models preparing for release and deployment.

From the page. wandb.ai, captured Oct 8, 2026

For our model training, having all the metrics in one place in W&B and comparing runs easily is so useful. Making sure we can do fire-and-forget and see all the metrics coming in has been super helpful. We’re tracking all the loss functions, evaluation metrics like precision, recall, and of course GPU usage metrics as well.

Philip Botros, ML Engineer, Captur. Source, captured Oct 8, 2026

What the story claims, and what we checked

We compared the story with its live page on Oct 8, 2026.

  • The passage quoted aboveCheckedCopied word for word from the page, near the name of Captur.
  • The publication dateCheckedRead from the page’s own metadata, never guessed.
  • Captur uses Weights & BiasesCheckedConfirmed line. Latest check across sources: Oct 8, 2026.
  • The result itselfNot checkedWe quote it; we did not measure it.

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