# How Nayya uses Labelbox

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

- Company: [Nayya](https://www.usedby.ai/companies/nayya.md)
- Tool: [Labelbox](https://www.usedby.ai/tools/labelbox.md)
- Teams: Actuaries, Customer Success

## What the story says

Nayya, an AI-first company that recommends employer benefit plans, uses Labelbox to produce labeled data for offline model training, live prediction evaluation, and expert verification. Its actuaries use Labelbox's Python SDK to see how the model generates predictions and to evaluate them.

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

> Nayya uses Labelbox as a data engine to train models faster through streamlined signal production and collaboration. For never-labeled data, a strong QA process speeds cataloging and extraction from disparate sources.

> The model-assisted workflow within Labelbox allows us to do this at scale and build a repeatable process for our data scientists as well as any subject matter experts that work with us,
>
> Ishan Babbar, lead data scientist at Nayya

## 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 Nayya.
- Checked: Nayya uses Labelbox. Confirmed line. Latest check across sources: 2026-10-07.
- Not checked: the result itself. We quote it; we did not measure it.

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