How Ramp engineers accelerate code review with Codex

Ramp, a fintech company, reported on the OpenAI Blog that its engineers have integrated OpenAI's Codex model (with GPT-5.5) into their code review process. By using Codex to automatically generate detailed feedback on pull requests, Ramp's developers can receive substantive reviews in minutes rather than hours. The system analyzes code changes, suggests improvements, and catches potential issues before human reviewers step in. Ramp found this workflow significantly reduces cycle time for code reviews, allowing engineers to iterate faster without sacrificing code quality. The approach combines Codex's understanding of code context with Ramp's own best practices and style guides, ensuring feedback aligns with company standards. For developers and teams building AI-powered workflows, this case shows how large language models can be applied to automate and accelerate a traditionally manual, time-consuming part of software development. It also highlights the importance of customizing AI outputs to specific team conventions rather than relying on generic suggestions.