AI CODEBASE AUDIT

Know exactly what's in
your codebase.

A fixed-price audit by a senior engineer who specializes in AI-assisted codebases. You get a detailed report, a walkthrough call, and a clear picture of what's actually in your code — not what you think is in it.

AI tools shipped your code faster. But faster isn't safer.

45% of AI-generated code contains security vulnerabilities
41% code churn — revised within two weeks of generation
91% increase in code review time since AI adoption
TRANSPARENT PRICING

Pick your depth.

Published pricing. No "contact us for a quote." You know what you're paying before we talk.

Quick Scan

$1,500

48-72 hour turnaround

  • Automated security & dependency scan
  • Focused expert review of highest-risk areas
  • AI-specific failure mode check
  • 3-5 page risk report
  • 30-minute walkthrough call

Best for: Solo founders, pre-launch MVPs, "is this safe to ship?"

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MOST POPULAR

Full Audit

$5,000

1 week turnaround

  • Everything in Quick Scan, plus:
  • Complete architecture review
  • Full codebase AI quality assessment
  • Performance analysis
  • 10-15 page report with code references
  • 60-minute walkthrough call
  • 30 days async support

Best for: Funded startups, products with payments or PII

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Strategic Audit

$10,000 – 15,000

2 week turnaround

  • Everything in Full Audit, plus:
  • Team & process assessment
  • 12-month architecture roadmap
  • Investor-ready technical summary
  • 30 days async support

Best for: Pre-fundraise, pre-acquisition, enterprise readiness

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THE DELIVERABLE

What you get.

1

Executive Summary

Health score (A-F), top risks, top strengths, launch readiness.

2

Security Assessment

Vulnerabilities by severity with exact file and line references.

3

Architecture Review

Component map, data flow, dependency graph, scalability assessment.

4

AI-Specific Findings

Hallucinated code, dead conditionals, context drift, type safety erosion.

5

Code Quality Scorecard

Complexity, test quality, naming, duplication, error handling.

6

Performance Analysis

Bottlenecks and optimization opportunities with estimated impact.

7

Production Readiness

Logging, monitoring, CI/CD, configuration management.

8

Prioritized Remediation Roadmap

Phased plan: Critical → Important → Improvement.

9

AI-Ready Fix Prompts

Copy-pasteable instructions for Cursor or Claude to implement each fix.

FROM A RECENT AUDIT

What was hiding in 100K+ lines of AI-generated code.

The AI hallucinated 6 out of 7 database field names.

numberOfDays instead of durationDays. googlePercentage instead of google. They look right in code review. They fail at runtime.

The AI wrote "[REDACTED]" as a string literal in production code.

Its safety training replaced "development" with "[REDACTED]" in a conditional check. The debug logging silently stopped working.

A single duplicate env var killed the entire CI pipeline.

AI-generated PRs kept shipping with zero automated checks running. The audit caught everything that went out during that window.

Users saw [object Object] in the campaign review screen.

The AI passed country objects into a .join(", ") meant for strings. The AI's own follow-up fix cast everything to any to make the error go away.

TikTok reach estimator showed 598 million daily users on a $50 budget.

The AI returned the total audience pool instead of budget-scaled reach. It doesn't understand your business domain.

Tests reported 88% coverage. Success paths never executed.

The test fixtures only recorded error responses. Every "passing" test was tautological.

Frequently Asked Questions

Your codebase has problems you don't know about yet.

A 30-minute call costs you nothing. What you don't know about your code could cost you everything.

Book Your Discovery Call