Omnia Fishing Optimizes Cross-Stack Development with CodeRabbit

At a Glance

Industry Vertical: E-commerce
Segment: SMB
Primary contact: Matthew Cox, Data Scientist
Coding languages: Javascript, Python, Ruby
Challenge: Slow, ineffective cross-stack code reviews.
Key Result: AI-powered code reviews improved efficiency and quality across diverse technology stacks.

About Omnia Fishing

Omnia Fishing is a cutting-edge e-commerce firm that delivers state-of-the-art web applications to improve the fishing experience in the Great Lakes area and beyond. Omnia Fishing serves anglers and fishermen by providing web-based tools and resources that simplify the planning and execution of successful fishing excursions. By combining an app-based mapping service with the ability to buy the right fishing gear and build a fishing strategy powered by a community of content creators, Omnia Fishing improves the fishing experience on the water.

Business Challenges

Omnia Fishing, an e-commerce company with a mobile app subscription for anglers, was growing fast but had a small engineering team. With engineers working across entirely different technology stacks, the company faced a critical challenge: ensuring code quality without relying on manual code reviews, which were often slow and challenging due to the difficulty of having developers unfamiliar with the specific technologies involved (e.g., a Ruby developer reviewing Python code) leading to either insufficient reviews or no reviews at all.

Key Challenges:

• Lack of Peer Reviews Across Stacks: two different engineering teams worked on different stacks and would review each other's code without expert knowledge of the other stack.

"It’s like having a second opinion without having someone on the same stack. It catches things I miss, and I don’t overlook important changes."

– Matthew Cox, Data Scientist, Omnia Fishing

CodeRabbit Benefits:

Omnia Fishing discovered CodeRabbit through the GitHub Marketplace and adopted CodeRabbit’s AI code reviews to address these pain points. The AI platform became a key asset for the engineering team, even in its initial implementation.

• Cross-Stack Code Review Support: CodeRabbit was a virtual team member, providing code reviews across different tech stacks and maintaining code quality. It found edge cases and optimizations, as said by Omnia’s data scientist: “It’s great at pointing out edge cases I hadn’t thought of or suggesting ways to simplify overly complicated solutions.”

• Reduced Cognitive Load: Engineers used AI code reviews to smooth out PR workflows, comment directly, and resolve systematically.

• Enhanced Efficiency for Small Teams: CodeRabbit sped up development and quality, especially in a small team where velocity counts.

• Repository-Specific Guidance: Omnia Fishing’s engineers tested CodeRabbit’s ability to adapt to repository-specific needs ranging from typescript to SQL-based stacks

Conclusion

CodeRabbit’s AI code reviews helped Omnia Fishing to solve the big problems as a small team working on multiple tech stacks. CodeRabbit was a virtual team member with expert-level knowledge and understanding of the multiple tech stacks used by Omnia Fishing.

AI code reviews improve code quality, reduce cognitive load, and speed up PR merge workflows. Edge case detection and optimization suggestions made sure they delivered high-quality code with minimal friction and AI replacing the first pass that would otherwise be done manually. Ultimately this allows Omnia Fishing to ship higher quality code in a shorter time with the same sized team.

Get Started with CodeRabbit

You can utilize the power of AI Code Reviews with CodeRabbit as well. It takes less than 5 minutes, and no credit card is required, to integrate CodeRabbit with your git platform. Start Your Free Trial, create a new pull request, and watch AI simplify your code reviews in just a few minutes. Questions? Reach out to our team for support.