Vibe coding cleanup services

AI-generated code made production-grade, not rewritten from scratch. We keep the features your users rely on and fix the foundation underneath them.
A free vibe code assessment to start

20+

years of engineering

270+

projects delivered

4.9

rating on Clutch

Our vibe coding cleanup services turn apps built with Cursor, Claude Code, Copilot, Lovable or Replit into secure, tested systems your team can own. We bring 300+ professionals, 40+ experts in math and physics, and two decades of untangling code that someone else wrote.

It works in the demo. Will it survive production?

AI-generated code holding you back?

Every fix breaks something else

Business rules, data access and UI are tightly coupled, so each change ripples into screens nobody touched.

Nobody can explain how it works

The logic came from prompts, not design decisions, and onboarding a new engineer takes weeks instead of days.

Security gaps hide behind working features

Hard-coded keys, unvalidated inputs and SQL queries pass every demo and fail the first real audit.

There is no safety net

Without adequate quality controls, users find the bugs first, and every release is a gamble on revenue and reputation.

It slows down as you grow

Duplicate queries, missing caching and tight coupling hold up at 50 users and stall at 5,000.

Dependencies you never chose

AI assistants pull in packages and snippets nobody vetted, so unvetted dependencies can expose the whole product.

Vibe code cleanup services

Code health audit

We map architecture, dependencies, test coverage and security gaps, then rank every issue by business risk.

Security hardening

We remove exposed secrets, add input validation and parameterized queries, and lock down authentication and access control.

Refactoring & restructuring

We separate business logic from UI and data access, remove duplication, and apply one consistent pattern across the codebase.

Automated testing

We add unit, integration and end-to-end tests to the flows that make you money, so regressions surface before users see them.

Performance & scalability

We fix slow queries, add caching, and remove bottlenecks so the app holds up under real traffic.

Dependency cleanup

We audit every package the AI pulled in, remove what you don’t need, and patch what you do.

CI/CD & release pipeline

We set up automated build, test and deploy steps so every release is checked before it ships.

Documentation & handover

We turn prompt-driven logic into architecture notes and runbooks your own team can maintain.

Vibe code cleanup strategies

ApproachBest when…
StabilizeThe app works but breaks unpredictably, and you need it reliable before the next release or funding round.
HardenThe product handles customer, patient or payment data and must pass a security review or compliance audit.
RefactorThe features are right, but the code is too tangled to extend without breaking something.
Re-architectThe structure itself blocks growth: the app can’t scale, integrate, or support more users and tenants.
Rebuild selectivelyA few core modules are beyond repair, while the rest of the product is worth keeping.
RebuildThe prototype proved the idea, but almost nothing in the code can carry the real product forward.

AI-assisted cleanup, with senior engineers in control

AI handles the volume: mapping dependencies, generating tests, drafting documentation and flagging anti-patterns across thousands of files. Our senior engineers set the architecture, verify every change against real behavior, and turn each recurring AI mistake into a standing rule.

AI writes fast. We make sure it’s right.

Get your codebase reviewed by an engineer

AI tools and platforms we clean up after

  • Cursor
  • Claude Code
  • GitHub Copilot
  • OpenAI Codex
  • Windsurf
  • Lovable
  • Bolt
  • Replit
  • v0
  • Supabase
  • Firebase
  • Next.js

Tech stack & standards

Backend

  • .NET 8/9/10
  • ASP.NET Core
  • C#
  • C++
  • Python
  • PHP
  • Node.js

Frontend

  • React
  • Angular
  • Vue
  • JavaScript
  • TypeScript

Infrastructure

  • Azure
  • AWS
  • Docker
  • Kubernetes
  • Terraform
  • Jenkins

Database

  • MS SQL
  • MySQL
  • PostgreSQL
  • Redis
  • Elasticsearch
  • MongoDB

Standards & compliance

  • HIPAA
  • GDPR
  • HL7
  • FHIR
  • DICOM

AI

  • OpenAI
  • LangChain
  • LangGraph
  • PyTorch
  • TensorFlow
  • scikit-learn

Case studies

RPA platform stabilization

RPA platform stabilization

Industry: IT & technology

Legacy code → modular architecture

An enterprise RPA platform had become unstable, rigid and expensive to upgrade, with bugs piling up in every release. We restructured it into modular components and set up engineering standards and CI/CD, while keeping backward compatibility for existing customers.

The results we achieved:

  • 10× faster system upgrades
  • 80% fewer automation bugs
  • Modular architecture
  • Cross-platform toolkit
READ FULL CASE STUDY
RPA platform stabilization
Platform re-architecture

Platform re-architecture

Industry: Healthcare

Web platform → cloud-native infrastructure

A popular fitness platform had outgrown its architecture, which blocked expansion to new channels and customers. We re-architected it into a cloud-native SaaS product while keeping its existing functionality and adding iOS, Android and third-party integrations.

The results we achieved:

  • 100× faster request processing
  • 1,000+ concurrent users supported
  • Cloud infrastructure
  • SaaS offering
READ FULL CASE STUDY

Abto Software’s vibe coding cleanup framework

1
Assess
We audit the codebase, data, dependencies and security posture, then deliver a ranked risk report and roadmap.
2
Secure
We prioritize critical vulnerabilities first: exposed secrets, open endpoints, injection risks and broken access control.
3
Prove
We refactor one representative module end to end, so you see the approach and the result before scaling it.
4
Refactor
We restructure the rest in small, tested increments, prioritized by business impact.
5
Validate
We verify behavior, performance, security and integrations against the original app before each release.
6
Hand over
We transfer documentation, tests and pipelines to your team, or stay on to support and evolve the product.

Vibe code cleanup without breaking what works

We understand before we change

We map how the app actually behaves — data flows, dependencies, edge cases — before touching a single critical component.

We lock in behavior before we refactor

Golden-master tests capture existing behavior, so every refactor is proven to change structure, not results.

Your product keeps shipping

Small increments, feature flags and phased rollout let your team release features while the foundation improves.

We fix one variable at a time

We separate refactoring from schema or data migrations, so any regression is traced in hours, not days.

We review every AI-generated line

Senior engineers check AI output against real behavior; agents get read-only data access and never commit or deploy.

We build in security

Authentication, authorization, input validation, secret management and dependency scanning are part of every increment, not a final step.

Stabilizing systems that run your business

Healthcare

  • Patient portals
  • Telemedicine platforms
  • EHR & EMR integrations
  • Practice management systems
  • Appointment scheduling apps
  • Remote patient monitoring apps
  • Laboratory information systems (LIS)
  • Clinical decision-support tools

Retail & e-commerce

  • E-commerce storefronts
  • POS systems
  • Order management systems (OMS)
  • Inventory management systems
  • Pricing & promotion engines
  • Loyalty & CRM platforms
  • Payment & checkout flows

Finance

  • Payment processing
  • Lending & loan origination apps
  • Underwriting platforms
  • Claims management
  • Customer onboarding & KYC flows
  • Fraud detection
  • Account management portals

Manufacturing

  • ERP add-ons & extensions
  • Manufacturing execution systems (MES)
  • Quality management systems (QMS)
  • Warehouse management systems (WMS)
  • Supply chain management (SCM)
  • Engineering & CAD tools

Logistics

  • Transportation management systems (TMS)
  • Warehouse management systems (WMS)
  • Fleet management platforms
  • Dispatch & delivery apps
  • Route optimization tools
  • Tracking & visibility dashboards

SaaS & internal tools

  • Multi-tenant SaaS products
  • Admin panels & back offices
  • Internal dashboards
  • CRM & sales tools
  • AI agent & chatbot backends
  • API platforms

Start where you are

1
Code health assessment
A fixed-scope audit of your AI-generated codebase.

You get: A ranked risk report and a cleanup roadmap before you commit to anything larger.
2
Stabilization pilot
We secure and clean up one critical module or user flow.

You get: A proven approach, measurable results, and a realistic estimate for the rest.
3
Full-cycle cleanup
From audit through refactoring, testing, CI/CD and handover — we take full ownership.

You get: A production-grade product your team can extend with confidence, plus optional ongoing support.

Clients

Ryan Fiorini
Ryan Fiorini linkedin
Co-Founder, CEO
https://blinkcns.com/

We had them on R&D projects we didn’t know how to move forward with. They not only created the work, it will be included in our patents. Abto turned our ideas into something tangible that we could use. We were so happy with their work that we decided to expand.

Christian Baumann
Christian Baumann linkedin
CEO
https://xa.com/

We rely a great deal on the IT services and expertise we receive from Abto. For us, it is one of our success factors to rely on a partner with a professional approach like Abto to be successful in our market segments.

Tony Clarey
Tony Clarey linkedin
VP of Business Development
https://euvic.com/

Abto Software meets the client’s expectations, and their end clients are satisfied with Abto Software’s work. They’ve established a personal relationship with the client that helps them resolve issues quickly. They maintain close communication with the client through Slack and in-person meetings.

Andreas Meier
Andreas Meier linkedin
Head of Product Development
https://enlotec.com/

We started to build a dedicated team in Lviv together with Abto Software 3 years ago. As a product vendor, we rely on resources that can build up knowledge about our products long-term. Abto was able to provide us with these services.

Philip Nussbaumer
Philip Nussbaumer linkedin
Head of Products
https://upgreat.ch/

Abto Software specialists developed a huge and extremely flexible SharePoint Client App for a Swiss customer providing various IT services, including the development of software based on SharePoint and its extensions.

Our partnerships and awards

FAQ

Timelines depend on codebase size, how much is AI-generated, and how much test coverage already exists.

  • Code health assessment: [1–2 weeks]
  • Critical security fixes: often within the assessment window
  • Stabilization pilot for one module or flow: [2–4 weeks]
  • Full cleanup of a typical product: [1–4 months]
  • Large, multi-service platforms: longer, delivered in increments

The assessment gives you a precise timeline before you commit to the full scope.

We follow six stages and validate the result at each one.

  • Assess the codebase, dependencies and security posture
  • Secure the critical vulnerabilities first
  • Prove the approach on one representative module
  • Refactor the rest in tested increments
  • Validate behavior, performance and integrations
  • Hand over documentation, tests and pipelines

You see working results after the pilot, long before the full scope is done.

Treat AI-generated code like any contribution from an unknown developer: review it, test it, and verify it against real behavior.

  • Audit before you refactor; never fix what you haven’t mapped
  • Capture current behavior with tests before changing structure
  • Close security gaps first: secrets, injection, access control
  • Change one variable at a time — code, schema or data, not all three
  • Pin and scan every dependency the AI introduced
  • Write down architecture decisions so the next prompt doesn’t undo them

We bake these into your workflow so new AI-generated code stays clean too.

A cleanup turns a fast prototype into an asset you can sell, scale and maintain.

  • Fewer production incidents and regressions
  • Faster feature delivery on a decoupled codebase
  • A security posture that passes customer and compliance reviews
  • Lower maintenance and onboarding costs
  • A product your own team understands and controls

Most teams recover the cleanup investment through faster, safer releases.

The biggest risk is breaking features users already depend on.

  • Lost behavior during refactoring — managed with golden-master tests
  • Hidden dependencies — managed by mapping before changing
  • Release freezes — avoided with small increments and feature flags
  • Data integrity issues — managed by never mixing code and data changes
  • Scope creep — managed with a ranked roadmap and fixed-scope pilot

Our free assessment shows which of these apply to your product before any work begins.

Contact us

Tell your idea, request a quote or ask us a question
We take ownership to make it a success — because we build what we’re proud of.
Yuriy Kapkovskyy linkedin
Chief Sales and Marketing Officer, Co-owner
star star star star star 4.9/5
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