Cursor accelerates development with AI pair programming. But AI-assisted code can accumulate architectural debt. We clean it up and deliver production-ready code via GitHub PR within 48 hours.
These are the exact problems Cursor users report when their apps fail to ship.
We diagnose the root cause, not just the symptom.
Cursor generates code in chunks — later additions sometimes override or conflict with earlier patterns.
Generated code inherits context from the specific project setup that does not generalize to production.
Code that passes locally has no test coverage to catch regression in production deployments.
Large files are split in ways that break imports and shared module references.
Generated code often lacks proper input sanitization and authorization checks for production.
Four steps from broken prototype to production-ready.
Link your GitHub repository — public or private. You control access and revoke it when work is done.
Our engineers analyze your codebase, identify the root causes, and provide a detailed assessment before any work begins.
Receive an instant transparent quote. You approve the scope and pricing before any code is written.
Working production-ready code arrives via GitHub PR within 48 hours. You review, merge, and ship.
Cursor is an AI coding assistant that helps you write code faster. The code it generates is context-aware and often impressive, but AI-assisted code accumulates patterns that do not always follow consistent architectural principles.
Each AI suggestion adds to the codebase — over iterations, patterns diverge and become inconsistent. We refactor for coherence.
Cursor adds imports liberally. We clean up unused dependencies and resolve circular imports.
Different parts of the codebase handle errors differently — we unify error handling for predictable production behavior.
AI often takes the quickest path — we replace shortcuts with proper abstractions that scale.