GenAI Code Review Copilot
Internal AI tool deployed at a 400-engineer fintech to automate security and compliance checks in PRs, cutting review cycle time by 55%.
Project Overview
A 400-engineer fintech company was struggling with code review bottlenecks. Senior engineers spent 30% of their time reviewing PRs — with no consistency, compliance checks missed in review, and junior engineers waiting 48 hours for feedback.
We built an AI-powered code review copilot that posts structured, actionable comments on every PR within minutes of opening — covering security, compliance, performance, and style.
The Challenge
Generic AI code review tools (like GitHub Copilot review) are too general — they don't understand the company's internal security policies, the specific risk surface of a payments codebase, or the organisation's architectural standards.
We needed to build a system that understood this company's rules: SOC2 control requirements, PCI-DSS data handling, proprietary API usage patterns, and historical PR patterns.
Architecture
PR Ingestion: GitHub App webhooks triggered review pipelines on each PR open and push event.
Context Assembly: For each changed file, we assembled: the diff, surrounding file context, the file's git history, the PR description, and relevant internal coding standards retrieved via semantic search.
Specialised Review Agents: We built four independent review agents, each with a focused system prompt and retrieval context:
- Security Agent: Checked for OWASP Top 10, injection vulnerabilities, secrets in code
- Compliance Agent: Validated PCI-DSS data handling, SOC2 control adherence
- Architecture Agent: Flagged deviations from internal API patterns and domain rules
- Performance Agent: Identified N+1 queries, memory leaks, and inefficient algorithms
Comment Generation: Each agent produced structured findings (severity, location, explanation, suggested fix) which were aggregated and posted as GitHub PR review comments.
Human-in-the-Loop: Engineers could approve, dismiss, or request clarification on AI findings. Feedback was logged for fine-tuning.
Results
- 55% reduction in PR review cycle time (48h → 21h average)
- 3x increase in security findings caught before merge
- Zero PCI violations in production in 12 months post-deployment
- Adopted as mandatory check across all engineering teams