The use case: how LeoLabs deploys CodeRabbit
LeoLabs uses CodeRabbit as an AI code review layer on pull requests, alongside mandatory human reviews, to keep code quality and security in step with faster AI-assisted development. It is configured with per-language and architecture instruction files and an OpenAI-only setup to meet defense procurement requirements.
In the customer’s words
If I tell my team to write four times as much code using AI, but the quality stays constant, then we're going to push four times as many bugs, have four times as many outages. If we want to go four times faster, we actually need four times better quality at least.Other companies using CodeRabbit
Customers across industries, with public evidence.
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Go straight to the source
Based on CodeRabbit’s published case study. We check the public evidence; the results are reported by the vendor.
coderabbit.ai- Last checked
- Oct 6, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 54.9%Checked
The figure is on the page; its label is our wording.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of LeoLabs.
- LeoLabs uses CodeRabbitChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
CodeRabbit differentiated itself by tracking context across separate repositories. In one trial instance, a competing tool flagged a false positive on a modified interface because it could not see the related repository. CodeRabbit evaluated both repositories, recognized the interface consistency, and cleared the change.