From vibe-coded MVP to production-ready engineering

Your MVP works. Now you need it to handle more users, pass investor scrutiny, and let other engineers work in it. That is what we do. Our senior engineers take your vibe-coded codebase, audit it end-to-end, handle technical debt remediation, and deliver production engineering services built around what already works.

Key numbers

Years of providing services
6 +
Satisfied clients
60 +
MVP & vibe-coded codebases audited and refactored
40 +
Certified Professionals
50 %
Client NPS
60 %

Our clients say

Total reviews

45+

Average rating

4.9

Source

This is for you if

Your MVP is live, and users are coming in, but performance degrades as the load increases

A new developer joined and spent weeks trying to understand the codebase

You have had a security incident, or you are starting to worry that you will

An investor or enterprise client asked about your technical infrastructure, and you did not have a confident answer

You are planning to raise and need to pass technical due diligence

Your team is shipping slower than six months ago, and the codebase is the reason

Our services

System behavior under load

We start with a full code audit: mapping how your codebase actually behaves across data flows, API contracts, and service dependencies, not how it was intended to behave.

Output: a written report with severity-ranked findings showing where the system holds and where it will not.

Security posture

AI code remediation starts here: authentication logic, secrets handling,
rate limiting, and access controls assessed against OWASP Top 10 and your compliance requirements.

Output: security vulnerabilities patched, compliance requirements met (HIPAA, GDPR, SOC-2, where applicable).

Technical debt remediation and refactoring

We identify what is solid, what is fragile, and what blocks scale or onboarding, then refactor incrementally while keeping business logic intact throughout.

Output: a refactored codebase with technical debt resolved and business logic intact.

Deployment reliability

We assess your current release process and introduce test coverage
for critical flows.

Output: a working CI/CD pipeline and automated tests; deployments are repeatable, not a manual checklist.

Performance and observability

Query patterns, caching strategy, and monitoring configuration reviewed against your SLA targets.

Output: monitoring, alerting, and observability tooling configured. Your team sees issues before users do.

Ownership and continuity

We document architectural decisions, operational runbooks, and onboarding paths.

Output: ADRs, runbooks, README standards. Engineers you bring in have what they need from day one.

Our production-readiness process

Discovery and Audit (Weeks 1-2)

Before any work begins, we run a full code audit. You get a written report with severity ratings. Nothing moves to the next phase until you have reviewed it and agreed on priorities.

Security and Structural Hardening (Weeks 3-4)

AI code remediation runs before refactoring for a specific reason: hardening code with security gaps compounds the risk. We close the security layer first, so phase three starts from a verified baseline.

Incremental Refactoring (Weeks 5-6)

Technical debt remediation runs against a now-secure codebase. Every change is validated against the original system behavior before it is merged. Nothing is replaced wholesale.

Testing, CI/CD, and Stress Test (Week 7)

Test coverage is written against the refactored system, not the original. The CI/CD pipeline is stood up and validated under real load before the system is declared production-ready.

Documentation and Engineering Handoff (Week 8)

ADRs, runbooks, and README standards are produced last, against the system as it exists after all changes, not as it was designed. Your team takes over a codebase that reflects what was actually built.

See how teams move from vibe-coded prototypes to production

Stasia Yasynyshyn and Stephan Moerman break down what it actually takes to turn a prototype into a product engineering teams can ship and maintain. Watch the full Ralabs Tech Talk on YouTube.

Why teams choose Ralabs for MVP development

No full rewrite

We refactor what exists. Your validated product decisions stay. Only what blocks production gets replaced.

Regulated industries

Healthcare and fintech are where most of our production deployments live. As an MVP development company operating in regulated environments, we know what HIPAA, GDPR, and SOC-2 actually require in a codebase.

Senior engineers, not generators

Every engagement is led by a senior engineer. Our AI services practice means we understand how these tools behave.
We apply judgment where it matters.

No lock-in

You own the code, the infrastructure, and the documentation. Every decision is recorded so your team can continue without us.

Our case studies

Let's review your codebase

Send us your repo overview. We will come back within one business day with an honest read on where you stand.

Yevhen Kulinichenko

Head of technology at Ralabs

FAQ​

Vibe coding is the practice of building software by describing what you want in natural language and letting AI tools generate the code. Platforms like Cursor, Bolt.new, Lovable, and Claude Code make it possible to ship a working product in days. The result is fast, but the generated code typically lacks test coverage, security review, proper CI/CD, and an architecture designed for scale. Production engineering is the process of closing those gaps before they become incidents.

Yes. AI MVP development services produce a distinct set of patterns: code that works in isolation but breaks at integration points, inconsistent error handling, and an architecture that made sense at the prototype stage but does not hold under load. The audit process is calibrated to these specific failure modes.

We will always do our best to avoid a full rewrite — it costs more and takes longer. But if the audit shows that refactoring would cost more than rebuilding, we will tell you that directly. The goal is the right outcome, not preserving the existing code at any cost.

The most frequent issues are improper input validation, insecure authentication patterns, secrets left in environment configs, missing rate limiting, and insufficient authorization logic. AI-generated code statistically carries more security vulnerabilities than human-written code. We review against OWASP Top 10 as a baseline and go deeper where your domain requires it.

Yes. We have production experience in both, and AI code remediation in regulated environments requires a different standard of review. We work to that standard by default.

AI code remediation is a structured review-and-repair cycle for AI-generated code, closing gaps in input validation, authentication, secrets management, and architecture before they reach production. It is not a rewrite. It brings generated code up to the standard of a human-authored production system.

The scope and budget are defined during the audit and agreed upon before any development begins. Cost depends on codebase size, number of services, and severity of findings — there is no fixed price before we see the system. What we can say: hardening an existing codebase consistently costs less than rebuilding it from scratch.

Let’s talk solutions

    By submitting this form, you agree to our Privacy Policy.



    Roman Rodomansky

    CTO & Co-Founder at Ralabs

    Andrii Yasynyshyn

    CEO & Co-Founder at Ralabs

    You got it right!

    Only 21% of people can identify an accessible visual.

    Your question