# How Intuitive uses Labelbox

**doubled**: “doubled the speed at which they deliver training signal for their multiple ML models”

As published on [labelbox.com](https://labelbox.com/customers/intuitive-surgical-customer-story/). Captured by usedby on 2026-10-07.

- Company: [Intuitive](https://www.usedby.ai/companies/intuitive.md)
- Tool: [Labelbox](https://www.usedby.ai/tools/labelbox.md)
- Teams: data science, clinical

## What the story says

Intuitive Surgical's data science team uses Labelbox to label surgical videos frame by frame for detecting and tracking instruments, with model-assisted workflows and a shared ontology across clinical and data science teams to train its computer vision models.

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

> The team scaled signal throughput, lowered the overhead of gathering performance and quality metrics, and doubled the speed at which they deliver training signal for their multiple ML models.

> We rely on collaborative software to help align our different teams such as our clinical teams and data science teams to ensure that we have a clearly defined ontology.
>
> Xi Liu, Manager of ML and Data Science

## What usedby checked

We compared the story with its live page on 2026-10-07.

- Checked: the figure doubled is printed word for word on the page, near the name of Intuitive.
- Checked: the passage quoted above is copied word for word from the page, near the name of Intuitive.
- Checked: Intuitive uses Labelbox. Confirmed line. Latest check across sources: 2026-10-07.
- Not checked: the result itself. We quote it; we did not measure it.

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Source: https://www.usedby.ai/case-studies/intuitive-surgical-labelbox · How we check: https://www.usedby.ai/methodology