ARTEMIS LAB / audit

AI-Built App Production Readiness

An application built with Claude Code, Cursor or Lovable can work in a demo without being ready for real users. We review what matters before launch: data access, critical workflows, operations and the ability to maintain the code.

Discuss this service →Custom quote based on size and criticality

Questions to answer before launch

Can a user view or change another account’s data? Are restrictions enforced on the server?
Do registration, payment and data-update workflows handle errors and repeated requests safely?
Can you detect an incident, restore data and return to a stable version?
Can your team understand and maintain the code beyond its first iterations?

Review the product that was built

Architecture, code quality, dependencies, environment configuration and separation of responsibilities.
Authentication, authorization, input validation, secrets and exposure of sensitive data.
Tests of priority workflows, error handling, logging, backups and deployment.
If the application uses an AI model: data flows, untrusted inputs, tool permissions and human approval for sensitive actions.

Examples of possible checks

Attempt access to a document using two test accounts to check user isolation.
Check whether a price or payment status can be changed in the browser without server-side validation.
Look for exposed keys, overly broad permissions and dependencies whose risk warrants remediation.
Test an external service failure or repeated operation in an agreed environment without disrupting users.

Deliverables for decisions and remediation

A leadership summary covering key risks, possible consequences and pre-launch decisions.
Documented findings with evidence, reproduction conditions and priority where relevant.
A remediation plan ordered by severity, effort and dependencies, with suggested fixes.
Unverified areas and review limitations, so an absence of findings is not mistaken for an absence of risk.

How the engagement works

1. Define use cases, users, processed data and the workflows that need protection first.
2. Collect agreed access to code, configuration and a test environment.
3. Combine automated analysis, human review and targeted checks within the agreed scope.
4. Walk through findings and agree next steps: fixes by your team, implementation support or a follow-up review.

Move from prototype to operations

Define what blocks launch, what can be fixed later and who owns each action.
Prepare validation criteria for fixes and essential business workflows.
Identify documentation, monitoring and handover needs for the maintenance team.
A technical review supports an informed launch decision; it is not a security or compliance certification.

Frequently asked questions

Does an AI-built application need a rewrite?

Not by default. We examine risks and the maintainability of existing code. Targeted fixes may be sufficient; a redesign needs evidence and a clear product rationale.

Can you review a prototype?

Yes, with a scope suited to its stage and intended use. The goal may be to prepare a safer pilot, plan launch or assess handover to a team.

Are fixes included?

The audit provides findings and a remediation plan. Fixes and verification are explicitly scoped in the engagement if you want them included.

What are the price and timeline?

They depend on application size, data sensitivity, available access and review depth. Scope and deliverables are agreed before work begins.

Prepare your application for its next step.

Tell us what the application does, how it was built and whether it is already in production. This will help us scope the review.

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