Case Study: Abnormal AI achieves faster, safer AI-native code review with CodeRabbit

Abnormal AI saves 100+ hours per month with CodeRabbit

Abnormal AI, an AI-powered cybersecurity company, faced a challenge as its 250 engineers adopted an AI-native development model. The rapid generation of code by AI agents and tools like Cursor was creating a bottleneck in human review, increasing the risk of subtle bugs, inconsistent standards, and security issues. They needed a way to enforce quality consistently without slowing down development.

The company implemented CodeRabbit as an automated enforcement layer for its pull requests. CodeRabbit reviewed both AI-generated and human-written code, automatically referencing internal documentation to provide high-quality feedback. The solution achieved a 65%+ acceptance rate on critical comments, catching issues like prompt injection vulnerabilities, and saved over 100 hours of reviewer time per month, allowing Abnormal AI to scale its development velocity without increasing risk.

Abnormal AI