What is an AI-built product audit?

An AI-built product audit is a structured review of an application created fully or partly with AI coding tools. It evaluates product logic, UX, architecture, code quality, security, QA, maintainability and production readiness.

Is this only a code audit?

No. Code is only one part of the review. Fourmeta also assesses the user journey, product logic, design quality, data flows, architecture and the team’s ability to maintain the product.

Can you audit an app built with Lovable, Bolt, Replit or Cursor?

Yes. We can review products created using prompt-to-app builders, AI coding environments or mixed human-and-AI development workflows.

What access do you need?

Typically, we need access to the product, source-code repository, relevant documentation and a test or staging environment. The final requirements depend on the agreed audit scope.

Do you provide penetration testing?

Not as part of the standard product audit. We review visible product and engineering security risks. Formal penetration testing or compliance work can be scoped separately with an appropriate specialist.

How long does the audit take?

A focused audit may take several working days. Larger applications with multiple roles, integrations or codebases require a longer review. The timing is confirmed before work begins.

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AI-built product audit for startups

Get a senior review of your AI-built app’s UX, architecture, security and production readiness. Know what to keep, refactor or rebuild.

Audit my AI-built product

The prototype works. But you are not sure what is hiding underneath.

Get your assessment

You do not need more features yet.
You need an honest assessment of what you already have.

Once real users arrive, the risks change:
‍

Authentication and permissions become critical

Payments and customer data must be protected

Edge cases start breaking the main workflow

Every new feature becomes harder to add

AI-generated code becomes difficult to understand

Investors or buyers begin asking technical questions

Nobody can confidently say whether to continue or rebuild

Fast to build does not mean ready to ship

phases

1.8× more high
severity findings

20% packages
may not exist

70% of vibe-coded projects had no test files

45% of reviewed
literature reported
short-term speed gains

1.8× more high
severity findings

20% packages
may not exist

70% of vibe-coded projects had no test files

45% of reviewed
literature reported
short-term speed gains

Production requires
more than a working flow.

Security, monitoring, backups, deployment, ownership, data protection and failure handling all become part of the product once it goes live.

Audit my AI built

One audit. Six product
critical perspectives.

01. Product logic

We review whether the product solves a clear problem and whether the core user workflow reflects the intended business model.

02. User experience

We assess whether real users can understand and complete the main actions without founder guidance.

03. Code and architecture

We assess whether the current codebase can support the next product stage.

04. Security and data

We identify visible launch risks around sensitive information and access.

05. QA and production readiness

We assess whether the product can be safely deployed, monitored and changed.

06. Team and delivery readiness

We assess whether the team can continue developing the product safely after the audit.

You will know what to do next.

By the end of the audit, you will have one of four clear outcomes:
‍
1. Launch with confidence
2. Launch after focused fixes
3. Refactor selected areas
4. Rebuild only where necessary

Schedule your audit

7+ years

In industry

20+

Developers

30+

completed AI audits

Our awards and recognitions

You receive a decision—not a list of problems.

We do not recommend rebuilding the whole product by default. The goal is to protect momentum while removing the risks that matter.

Keep

What already works and should remain unchanged.

Fix now

Critical issues that should be resolved before launch, customer onboarding or fundraising.

Refactor next

Areas that can function temporarily but will limit future delivery or scale.

Rebuild (partly)

Components where repairing the current implementation would be slower or riskier than replacing it.

Build later

Features and infrastructure that are unnecessary at the current product stage.

What you get right after?

Schedule your audit

When should you audit an AI-built product?

Audit my product

Before launching to real users

Before introducing payments

Before fundraising

Before selling to larger customers

When development is slowing down

When nobody trusts the codebase

Before hiring a development team

Built with AI? We can review it.

The audit is not limited to one tool. 
We review the resulting product and codebase—not the logo used to generate it.

Loveble

Bolt

Replit

Cursor

Claude AI

v0

Windsurf

Github copilot

Automated scanner

AI product generation for fashion brands

Reviews code patterns

Produces technical alerts

Sees individual files

Flags everything equally

Cannot evaluate UX

Ends with a report

Book an audit

Fourmeta AI-Built
Product Audit

AI quiz & chatbot platform

Reviews the complete product

Explains commercial and product impact

Reviews workflows and architecture

Prioritises by risk and product stage

Includes product and UX review

Ends with a practical delivery plan

A focused audit without slowing down the team

Initial fit check

Access and scope

Product and technical audit

Findings and recommendations

Review session

We explain the findings and agree on the safest, fastest next step.

Schedule your audit

2026

Fourmula AI

Fourmeta designed and developed Fourmula.ai across product strategy, brand, UX, AI workflows and engineering. That experience allows us to assess whether an AI-built product works as a coherent customer experience—not simply whether the code passes automated checks.

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We understand AI products beyond the codebase.