Inconsistent quality
Code from different people and AI workflows may lack a shared engineering standard.
In development · Open to partners and investors
AI Code Quality Intelligence
AuditorX
Understand code quality and risk before production
AuditorX is a platform for analyzing code quality, maintainability, and AI-assisted development risk—with a Vibe Code Score and AI Skills that guide AI toward disciplined software engineering practices.
For development teams, tech leads, and organizations adopting AI coding
Repository scan
product-api / main
Quality
82/100
Maintainability
74/100
Vibe Code
36/100
18async function createOrder(input) {
19const result = await db.query(input)
!Validate input before the database boundary
20return result
Explainable findings · Human review encouraged
The problem
Code is created faster, but confidence does not scale with it
AI accelerates delivery, yet code that appears to work can hide technical debt, security concerns, and patterns that are difficult to maintain.
Risk discovered too late
Architecture and security issues often surface only as the system becomes complex.
Missing AI guardrails
Generic prompts do not give AI the context of an experienced software engineer.
The AuditorX approach
Turn repository signals into decisions teams can act on
AuditorX aims to combine code analysis, risk explanations, and practical improvements in one experience. The Vibe Code Score is not presented as a percentage of AI-generated code.
Code quality analysis
Surface code smells, duplication, and maintainability concerns.
Maintainability and debt
Prioritize areas that could become expensive long-term constraints.
Security signals
Highlight risks that deserve deeper review from the team.
Vibe Code Score
Assess signals of rapid development without sufficient engineering guardrails.
Actionable recommendations
Explain likely impact and suggest improvements teams can plan.
AI Engineering Skills
Guidance for architecture, testing, security, and AI-assisted code review.
Who it is for
Built for teams adopting AI without lowering engineering standards
Software development teams
Tech leads and engineering managers
Software houses and startups
Organizations adopting AI coding tools
Product roadmap
Start with explainable analysis, then become an engineering guardrail
We plan to test scoring and recommendations across varied repositories and make the assessment principles transparent.
Research
Define quality signals, evaluation criteria, and the Vibe Code Score scope.
Scanner MVP
Analyze repositories and produce the first code quality report.
Team pilot
Test with development teams and refine accuracy and explanations.
Engineering platform
Connect workflows and expand the AI Engineering Skills library.
Investment opportunity
Help build the trust layer for software in the AI era
AuditorX is looking for investors, pilot engineering teams, and software quality experts who want to shape a new standard for AI-assisted development.
AI coding adoption is moving faster than quality assurance
Potential across analysis tooling and reusable Engineering Skills
Trust built through explainable and reviewable findings
Frequently asked questions
Get to know AuditorX
Building with AI and looking for more confidence?
Help define the code quality standard for the AI era with AuditorX.
Contact the AuditorX team