# How Ancestry uses Labelbox

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

- Company: [Ancestry](https://www.usedby.ai/companies/ancestry.md)
- Tool: [Labelbox](https://www.usedby.ai/tools/labelbox.md)
- Teams: Data Science

## What the story says

Ancestry's data science team uses Labelbox's model-assisted labeling and native image and text editors to produce training signal for models that extract genealogical data from historical records. Domain experts take part in the feedback and review loop, which supports a weekly model iteration cycle.

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

> Ancestry adopted Labelbox’s model-assisted data workflows, combining automated labeling with expert human feedback directly within native image and text editors. This approach accelerated signal generation while enabling domain experts to actively participate in data processing and review.

> Before Labelbox, we could train a model pretty quickly and evaluate against validation test sets, but getting data processed and reviewed took forever. Having a strong collaborative expert feedback service helped us get to a weekly iteration cycle
>
> Stanley Fujimoto, Data Scientist at Ancestry

## What usedby checked

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

- Checked: the passage quoted above is copied word for word from the page, near the name of Ancestry.
- Checked: Ancestry 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/ancestry-labelbox · How we check: https://www.usedby.ai/methodology