# How Notion uses Anyscale

**2-3x**: “2-3x faster deployment”

As published on [anyscale.com](https://www.anyscale.com/resources/case-study/notion). Captured by usedby on 2026-10-07.

- Company: [Notion](https://www.usedby.ai/companies/notion.md)
- Tool: [Anyscale](https://www.usedby.ai/tools/anyscale.md)
- Industry: [DevTools & Infrastructure](https://www.usedby.ai/companies/industry/devtools-infrastructure.md)
- Teams: Search, AI Modeling

## What the story says

Notion runs inference for its machine-learning search reranking models on Anyscale, using Ray to scale horizontally while keeping latency low for its AI-powered Enterprise Search. It also uses Anyscale for blue-green model deployments and is looking at it for embedding generation.

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

> With Anyscale, we've achieved 20% better latency compared to our previous solution – all while supporting continued user growth.

- **20%**: “20% better latency”
- **2 months**: “2 months to migrate all workflows to Anyscale”

> With Anyscale, we've achieved 20% better latency compared to our previous solution – all while supporting continued user growth.
>
> Jake Sager, Software Engineer

## What usedby checked

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

- Checked: the figure 2-3x is printed word for word on the page, near the name of Notion.
- Checked: the passage quoted above is copied word for word from the page, near the name of Notion.
- Checked: Notion uses Anyscale. 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/notion-anyscale · How we check: https://www.usedby.ai/methodology