The Problem
Your team uses Claude Code or Copilot to ship faster, but AI agents ignore your architectural patterns. They create new database queries instead of using your service classes, put business logic in the wrong layer, and violate layer boundaries. Each fix is small, but across a team of 8 engineers, refactoring agent-generated code becomes a constant tax that bleeds productivity.
What We're Building
CodeGuard automatically extracts your codebase architecture—service classes, query patterns, layer boundaries—and feeds it to AI agents in real-time. When an agent tries to violate your patterns, CodeGuard flags it, suggests the correct abstraction, and learns your team's style over time. It integrates into your CI/CD pipeline and dashboard, showing you exactly where agents are drifting and how much refactor work you're avoiding.
Who It's For
Engineering leads and staff engineers at mid-sized SaaS companies (20–100 engineers) and dev shops actively using Claude Code or GitHub Copilot as their primary coding tool.
Key Features
- Auto-extract service classes, query patterns, and layer boundaries from your git repo
- Real-time rule enforcement in Claude Code and GitHub Copilot via system context injection
- Pre-commit flagging: agents can't violate your patterns before code reaches your repo
- Alignment dashboard: track how often agents follow your rules and measure refactor savings
- One-click CI/CD integration: GitHub Actions, GitLab, or custom webhooks
We're validating this concept. When Claude or Copilot generates code that works but violates your patterns, how much time does your team spend refactoring it back in line per week?
By Jenavus — AI-powered business intelligence
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