Visma uses CodeRabbit as a code-review AI on large legacy codebases
Visma needed a code-review AI for large codebases with complex interdependencies in legacy code. The official case study describes how the company used CodeRabbit to enhance code quality and streamline reviews.
- Agent or tool
- CodeRabbit
- Topic
- Software Development
- Reported on
- Case study (CodeRabbit)
- Added
- 2026-11-14
Why it matters
Coding agents are moving from autocomplete to doing whole tasks: reading a codebase, making a plan and changing many files. This case is a concrete example of where that works in practice. It is one of 221 sightings filed under Software Development on Agent Sightings (number 33 by interest), and one of 6 involving CodeRabbit.
How you could try it
Here is a reusable prompt, written by us in our own words, that captures the task. Paste it into CodeRabbit or any similar agent and adjust the details to your situation.
I want a coding agent to take on work like this across our repositories, show its plan, and wait for review before anything merges. The tool in the source case was CodeRabbit.
Tip: Work on a fresh branch, ask for a plan before edits, and review the diff and test results before merging.
Source
Read the original first-hand account on Case study (CodeRabbit): https://coderabbit.ai/case-studies/how-visma-found-the-enhance-code-quality-and…. Our summary is a paraphrase; details are in the source.
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