# How DocsBot uses Weaviate

**50,000+**: “SCALED TO 50,000+ TENANTS IN A SINGLE CLUSTER”

As published on [weaviate.io](https://weaviate.io/case-studies/docsbot). Captured by usedby on 2026-10-02.

- Company: [DocsBot](https://www.usedby.ai/companies/docsbot.md)
- Tool: [Weaviate](https://www.usedby.ai/tools/weaviate.md)

## What the story says

DocsBot ingests, chunks and embeds customer documentation, then stores the vectors and metadata in Weaviate Cloud. At query time Weaviate provides semantic and hybrid search, and the retrieved context is passed to large language models to generate answers, with each customer's data kept in its own isolated tenant.

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

> DocsBot scaled retrieval with Weaviate Cloud to handle massive query volume, directly enabling DocsBot’s core business.

> Weaviate stood out because it’s clearly designed for real production use cases, not just experimentation. It was the only solution with an efficient tenant-based system that scaled to our unique workload of tens of thousands of distinct segmented indexes.
>
> Aaron Edwards, Founder of DocsBot

## What usedby checked

We compared the story with its live page on 2026-10-03.

- Checked: the figure 50,000+ is printed word for word on the page, near the name of DocsBot.
- Checked: the passage quoted above is copied word for word from the page, near the name of DocsBot.
- Checked: DocsBot uses Weaviate. Confirmed line. Latest check across sources: 2026-10-02.
- Not checked: the result itself. We quote it; we did not measure it.

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