AI coding tools can move fast, but they do not tell you whether the code is secure, maintainable, observable, or ready for real users. I review and harden software built with tools like Claude Code, Codex, Cursor, Lovable, and Replit so founders, agencies, and small teams can launch with confidence.
Most teams start with an AI Codebase Audit: a fixed-scope review that gives you a production-readiness score, prioritized engineering risks, and a clear plan for what to fix first.
Usually completed in about a week. Fixed price: $5–9k. First scoping call is free.
“The checkout flow works in testing, but failed payments are not handled, duplicate orders can be created, and there’s no alert when something breaks. Fixable, but not something you want to discover from your first real customers.”
the kind of thing I keep running into
A fixed-scope review for AI-built or AI-assisted codebases. I assess architecture, security, dependencies, testing, deployment readiness, and production risk, then give you a prioritized report with a score, the issues that matter most, and a practical plan to fix them.
A focused sprint to fix the highest-risk issues before launch, handoff, demo day, or a fundraise. I help stabilize the parts of the product that cannot fail: authentication, payments, data integrity, error handling, observability, deployment, and core user flows.
Ongoing senior engineering support for teams building with AI. Use it for pull-request review, architecture decisions, technical risk calls, agent workflow design, and the guardrails that keep AI-assisted development from turning into expensive rework.
A discreet senior review layer for agencies shipping AI-assisted client work under real deadlines. I help catch architectural, security, reliability, and maintainability issues before they reach the client, without slowing the team down.
Every audit is scored through PRISM: Production, Reliability, Integrity, Simplicity, and Maintainability.
Can the app deploy, roll back, and recover safely? Do critical flows fail gracefully? Are auth, permissions, payments, and business rules correct? Is the system simple enough to change? Can the next engineer understand it without reverse-engineering the codebase?
You leave with a readiness score, ranked risks, and a hardening plan, not a vague list of recommendations.
Read the full PRISM framework breakdown.
Mati Systems is run by Jonathan Jaime.
I’ve spent years working inside other people’s codebases, and I kept seeing the same problem: software that looked finished, but wasn’t built to survive real users.
That is why I started Mati Systems: to help teams catch those issues early, before they become expensive production problems.
Mati Systems reviews, hardens, and governs AI-assisted software so it is not just fast to build, but reliable, maintainable, and safe to operate.
I also build Mati, an open-source guardrail system for AI coding agents that helps repositories protect critical files, enforce project-specific rules, and prevent avoidable agent mistakes.
Not by default.
AI coding tools can generate working software quickly, but they do not reliably verify that the system is safe, maintainable, or ready for production. Common risks include duplicated business logic, fragile auth flows, missing failure handling, weak test coverage, unsafe deployment paths, and files that become too large or risky to change.
A senior engineering review catches those issues before users, clients, or investors do.
An AI codebase audit is a fixed-scope engineering review of an application's architecture, security, dependencies, testing, and production readiness.
Mati Systems reviews the codebase, identifies the real risks, ranks them by priority, and gives you a clear hardening plan. The goal is not a generic checklist. It is to answer one practical question: what needs to be fixed before this software is trusted with real users?
You get a written engineering report with a production-readiness score, the highest-risk issues ranked in priority order, and a clear hardening plan for what to fix first.
The audit covers architecture, auth, payments, data handling, deployment, testing, dependencies, maintainability, and AI-generated code quality. The goal is to give you a practical decision document: what is safe to ship, what is risky, and what needs to change before real users depend on it.
Any founder, agency, or team shipping an AI-built MVP before a launch, client handoff, investor demo, or production rollout should get an engineering review first.
Mati Systems runs that review as a PRISM audit: production readiness, reliability, integrity, simplicity, and maintainability. You leave knowing what is safe, what is risky, and what should be fixed first.
Every audit is organized around five questions:
Can it deploy and roll back safely?
Does it fail gracefully?
Are auth, data, and business logic correct?
Is it simple enough to change?
Will the next engineer understand it?
Those answers become a production-readiness score and a prioritized hardening plan.
A standard Mati Systems AI Codebase Audit is fixed-price at $5,000–$9,000 and typically takes about one week.
The first call is free and is used to scope the engagement. Pricing depends on codebase size, production complexity, and how much AI-generated or AI-assisted code needs to be reviewed.
The audit is designed to cost less than discovering a payment, auth, deployment, or data-handling issue after real users are already in the system.
Mati is an open-source guardrail system for AI coding agents.
It helps repositories protect critical files, encode project-specific engineering rules, and stop agents from making avoidable changes before they touch sensitive parts of the codebase.
Mati is built by Mati Systems, licensed under MIT, and available on GitHub.
Built with Cursor, Claude Code, Codex, Lovable, or Replit?
See how the audit changes based on the tool used to build your app.
Founder, agency, or engineering team?
See what Mati Systems checks for in your specific situation.
Built something fast with AI and not sure it’s ready?
Already shipped and worried the codebase may not hold up?
I’ll review the system, identify the real production risks, and show you what to fix first, whether you’re preparing to launch, handing off to a client, raising money, or supporting live users.
Email hello@matisystems.com for a free 20-minute call. No pitch, no obligation. I usually reply the same day.
I take on a limited number of audits each month to keep turnaround at about a week. Reach out early if your timeline is tight or your live product needs a senior engineering review.