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AI Code Review

AI Code Cleanup Services

AI code cleanup services transform AI-generated code into production-ready systems. Studies show 40% of AI-generated code contains security vulnerabilities. We find and fix SQL injection, hardcoded secrets, missing validation, and the architectural shortcuts that create technical debt.

AI Code Has Blind Spots

Copilot, Cursor, and ChatGPT generate functional code. But functional is not the same as secure, maintainable, or production-ready.

What AI Gets Wrong

  • SQL queries built with string concatenation
  • API keys and secrets hardcoded in source
  • User input passed directly to eval() or exec()
  • Auth tokens stored in localStorage
  • No rate limiting on sensitive endpoints
  • Catch-all error handlers that swallow failures

What We Fix

  • Parameterized queries and ORM integration
  • Environment variables and secret management
  • Input sanitization and validation layers
  • Secure cookie-based session handling
  • Rate limiting and abuse prevention
  • Structured error handling with proper recovery

What We Review and Fix

A systematic audit covering security, architecture, and code quality. Not just linting. Actual engineering review.

Security Vulnerabilities

SQL injection, XSS, hardcoded secrets, missing input validation, insecure deserialization. The stuff that gets you breached.

Architecture Issues

AI generates code that works in isolation. We fix the coupling, circular dependencies, and missing abstractions that make maintenance painful.

Error Handling

AI code often catches errors and silently fails or logs and continues. We add proper error boundaries, retries, and failure modes.

Test Coverage

AI writes tests that test the implementation, not the behavior. We add meaningful tests that catch regressions and document intent.

Code Quality

Consistent naming, proper typing, no magic strings, no copy-paste duplication. Code your team can actually maintain.

Documentation

AI generates verbose comments that explain what code does. We add documentation that explains why and how to use it.

Our Audit Process

Structured review by senior engineers. Clear findings. Actionable fixes.

1

Codebase Assessment

We review your repository structure, identify AI-generated sections, and scope the audit based on risk areas.

2

Security Analysis

Static analysis tools plus manual review. We check for OWASP vulnerabilities, dependency issues, and auth problems.

3

Architecture Review

Evaluate code organization, coupling, and patterns. Identify technical debt that will slow you down later.

4

Report and Fix

Detailed findings with severity ratings. We can fix the issues ourselves or guide your team through remediation.

Industries That Need This Most

Regulated industries where security vulnerabilities have real consequences.

Fintech & Crypto

Financial code needs more than functional correctness. PCI compliance, audit trails, and transaction integrity are non-negotiable.

Healthcare

HIPAA compliance, data encryption, access controls. AI doesn't understand healthcare regulations. We do.

Enterprise SaaS

Multi-tenant isolation, rate limiting, proper authentication. The infrastructure code AI consistently gets wrong.

Why Hexmount for Code Cleanup

We build systems that handle real money and real regulations. We know what production code requires.

Senior Engineers Only

Your code is reviewed by engineers with 5+ years of experience. No juniors learning on your codebase.

Production Experience

We have built cryptocurrency exchanges, fintech platforms, and government systems. We know what breaks at scale.

Direct Communication

No account managers or project coordinators. Talk directly to the engineers reviewing your code.

Fix, Not Just Find

We don't just hand you a list of problems. We fix them, or we pair with your team to fix them together.

Get Your AI Code Reviewed

Send us your repository. We will identify the security vulnerabilities and architectural issues, then give you a clear path to production-ready code.

Typical turnaround: 3-5 business days for initial assessment.