# How kapa.ai uses Weaviate

**7 days**: “The team built the first working version of their service with Weaviate in just 7 days”

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

- Company: [kapa.ai](https://www.usedby.ai/companies/kapa-ai.md)
- Tool: [Weaviate](https://www.usedby.ai/tools/weaviate.md)
- Industry: [Artificial Intelligence](https://www.usedby.ai/companies/industry/artificial-intelligence.md)

## What the story says

Kapa uses Weaviate as its core vector database and embeddings layer for an AI platform that turns technical documentation into support chatbots that answer product questions. It relies on Weaviate's hybrid search, Docker support and multi-tenancy to scale across nodes.

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

> Kapa chose Weaviate for several key reasons: Docker Compatibility: Weaviate's ability to run in Docker containers was crucial for their deployment and local development needs, unlike alternatives such as Pinecone.

- **100**: “Kapa has over 100 leading companies as customers including Docker, OpenAI, Monday.com, Grafana, and Reddit.”

## What usedby checked

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

- Checked: the figure 7 days is printed word for word on the page, near the name of kapa.ai.
- Checked: the passage quoted above is copied word for word from the page, near the name of kapa.ai.
- Checked: kapa.ai 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/kapa-weaviate · How we check: https://www.usedby.ai/methodology