The most widely-used AI code completion tool

Built with GitHub Copilot?
Let's make sure it's production-ready.

GitHub Copilot provides inline code suggestions and completions within existing IDEs. Unlike agent-based tools, it works within your existing codebase but can introduce inconsistencies and security issues through individual completions. We help non-technical founders identify and fix the issues AI tools leave behind.

JavaScriptTypeScriptPythonJavaGoRuby

Common issues we find in GitHub Copilot code

These are real problems we see in GitHub Copilot projects during our audits - not hypotheticals.

highSecurity

Insecure code patterns from training data

Copilot sometimes suggests patterns from its training data that are known to be insecure - like using eval(), innerHTML, or outdated crypto functions.

highSecurity

Hardcoded secrets in suggestions

Copilot occasionally suggests placeholder API keys or credentials that look real and get committed to version control.

lowCode Quality

Inconsistent code style across files

Different completions use different patterns - sometimes callbacks, sometimes async/await, sometimes .then(). The codebase becomes inconsistent over time.

mediumBugs

Subtly incorrect logic

Copilot completions often look correct but contain off-by-one errors, wrong comparison operators, or missed edge cases that cause intermittent bugs.

mediumBugs

Deprecated API usage

Copilot suggests code using deprecated APIs or outdated library versions from its training data, introducing compatibility and security issues.

lowPerformance

Unnecessary dependencies

Copilot suggests importing libraries for operations that could be done with native APIs, increasing bundle size and attack surface.

mediumDeployment

No deployment awareness

Copilot completes code in isolation without understanding the deployment context. Production-specific concerns like env vars and build optimization are missed.

mediumTesting

Generated tests with poor assertions

Copilot-generated tests often have weak assertions (checking that a function 'doesn't throw' rather than checking actual output), providing false confidence.

Start with a self-serve audit

Get a professional review of your GitHub Copilot project at a fixed price. Results reviewed by experienced engineers.

Security Review

Automated Security Scan

$19

AI-powered analysis of your codebase. Get a detailed report with prioritized findings within 24 hours.

Get Started
Most Popular

Security Review

Manual Security Review

from $250

Expert engineer works on your project directly. Fixed scope, fixed price, no surprises.

Get a Quote

Security Review

Full Pentest

Custom

Enterprise-grade engagement tailored to your needs. Dedicated engineer, ongoing support.

Fix Bugs

Code Audit

$19

AI-powered analysis of your codebase. Get a detailed report with prioritized findings within 24 hours.

Get Started
Most Popular

Fix Bugs

Bug Fixing

from $200

Expert engineer works on your project directly. Fixed scope, fixed price, no surprises.

Get a Quote

Fix Bugs

Ongoing Support

Custom

Enterprise-grade engagement tailored to your needs. Dedicated engineer, ongoing support.

Refactor Code

Code Audit

$19

AI-powered analysis of your codebase. Get a detailed report with prioritized findings within 24 hours.

Get Started
Most Popular

Refactor Code

Refactoring

from $400

Expert engineer works on your project directly. Fixed scope, fixed price, no surprises.

Get a Quote

Refactor Code

Full Rewrite

Custom

Enterprise-grade engagement tailored to your needs. Dedicated engineer, ongoing support.

100% of your audit purchase is credited toward any paid service. Start with an audit, then let us fix what we find.

How it works

1

Tell us about your app

Share your project details and what you need help with.

2

Expert + AI audit

A human expert assisted by AI reviews your code within 24 hours.

3

Launch with confidence

We fix what needs fixing and stick around to help.

Frequently asked questions

Is Copilot-assisted code less secure?

Research shows Copilot can introduce security vulnerabilities through insecure patterns from training data. A security review is especially important for Copilot-heavy codebases.

Can you audit a codebase that used Copilot extensively?

Yes. We look for the specific patterns Copilot introduces - inconsistent error handling, insecure suggestions, and deprecated API usage throughout the codebase.

How do I make my Copilot code production-ready?

Focus on consistency, security review, and testing. We standardize patterns across the codebase, fix security issues, and add test coverage for critical paths.

Is Copilot better or worse than agent-based AI tools?

Different risks. Copilot gives you more control but introduces inconsistencies. Agent-based tools produce more consistent code but with less oversight. Both need review.

Should I stop using Copilot?

No - Copilot is a great productivity tool. Just treat its suggestions as starting points that need review, not finished code. Pair it with periodic code audits.

Get your GitHub Copilot app production-ready

Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.

Tell Us About Your App