Codebase review
Assess structure, dependencies, configuration, duplicated logic and the main technical risks.
AI app rescue
Fix and deploy AI-generated web or mobile app code
Built an app with Cursor, Claude Code, Codex, Lovable, Bolt, Replit, v0, Base44 or ChatGPT and got stuck? Nezore reviews the code, diagnoses the real problems, fixes agreed issues and helps move the project toward a stable production deployment.
- Code types
- Web + mobile
- Primary focus
- Production readiness
- Experience
- 5+ years
From prototype to production
A controlled code rescue process
- 01Repository, errors and environment review
- 02Issue diagnosis and repair plan
- 03Code fixing, cleanup and testing
- 04Deployment and technical handover
We do not promise that every generated codebase is worth saving. The first step is to assess the current state and recommend the cleanest path forward.
What we fix
Common problems in AI-generated applications
Fast code generation is useful, but incomplete architecture, hidden assumptions and inconsistent code often appear when the prototype becomes a real product.
Bug fixing and debugging
Trace runtime errors, build failures, broken features and inconsistent application behavior.
Frontend and routing issues
Repair broken UI, navigation, forms, state, responsive layouts and component behavior.
API and database problems
Fix backend endpoints, data flow, validation, authentication and database connectivity.
Deployment blockers
Resolve environment, build, server, domain and platform issues preventing a stable release.
Refactoring and cleanup
Improve unstable areas, error handling and maintainability where the agreed scope allows.
Who this is for
For builders who have a prototype but need engineering support
This service is most useful when there is an existing repository, a clear intended workflow and specific problems to investigate.
Non-technical founders
Get an honest assessment of what works, what is broken and what should be fixed first.
AI-assisted developers
Resolve difficult bugs, architecture problems, integration issues and deployment blockers.
Startups with prototypes
Turn a demonstration into a more stable MVP through a structured repair process.
Agencies and internal teams
Get extra capacity for reviewing and recovering an AI-generated client or internal project.
Supported work
Web, mobile, backend and deployment recovery
The exact repair scope is defined after reviewing the repository and current failure points.
- ✓Cursor, Claude Code and Codex projects
- ✓Lovable, Bolt, Replit, v0 and Base44 apps
- ✓React, Vue, Next.js and Nuxt.js
- ✓Angular and Tailwind CSS
- ✓Node.js, Express.js and NestJS
- ✓Laravel and Python backends
- ✓React Native and Flutter apps
- ✓Supabase and Firebase
- ✓MongoDB and PostgreSQL
- ✓Authentication and user roles
- ✓Vercel, Netlify and server deployment
- ✓Environment variables and build configuration
Ways to start
Begin with diagnosis before committing to a large repair
The first review determines whether the best option is a small fix, a focused recovery sprint or a controlled rebuild.
Assessment
Code rescue audit
Understand the current state and the cleanest next step.
- •Repository review
- •Error reproduction
- •Risk and blocker list
- •Recommended fix plan
Common starting point
Repair sprint
Fix and deploy
Resolve an agreed group of issues and prepare a working deployment.
- •Bug and configuration fixes
- •API or database repair
- •Testing of main flows
- •Deployment support
Recovery
Production cleanup
Stabilize a larger codebase through prioritized engineering work.
- •Focused refactoring
- •Error handling improvements
- •Critical workflow testing
- •Handover and next-step plan
A code review is required before confirming whether the existing project can be repaired within the expected budget and timeline. View our pricing approach.
Our process
A practical path from broken code to a working release
The work is prioritized around reproducible problems and agreed acceptance criteria.
- Step 1
Code and requirements review
Review the repository, intended workflow, error reports, environment and deployment target.
- Step 2
Issue diagnosis
Reproduce failures and identify the root causes, dependencies and technical risks.
- Step 3
Repair plan
Agree which issues will be fixed, what will not be changed and how success will be tested.
- Step 4
Code fixing and cleanup
Repair the agreed frontend, backend, database, authentication or configuration problems.
- Step 5
Testing and deployment
Test the main workflows, create a production build and deploy to the agreed environment.
- Step 6
Handover
Document the work completed, setup requirements and recommended future improvements.
Technology
Stacks commonly recovered and deployed
Support depends on the specific repository and technologies involved, but the service covers common modern full-stack and mobile stacks.
CursorClaude CodeCodexLovableBoltReplitv0ReactVue.jsNext.jsNuxtAngularNode.jsNestJSLaravelReact NativeFlutterSupabaseFirebaseMongoDBPostgreSQLVercelNetlifyDocker
Why Nezore
Full-stack experience beyond prompt-generated code
Repairing generated code requires understanding the whole system: UI, backend, data, security, deployment and the intended business workflow.
- Hands-on frontend, backend, mobile, API and database development
- Experience with production deployments, environment configuration and long-term feature work
- Structured code review focused on root causes rather than random patches
- Ability to continue into maintenance, feature development or a controlled rebuild where needed
FAQ
Questions about AI-generated code repair
Which AI coding tools do you support?
We can review projects built or assisted by tools such as Cursor, Claude Code, Codex, Lovable, Bolt, Replit, v0, Base44 and ChatGPT. The underlying framework and codebase determine the exact support.
Can every AI-generated project be fixed?
No. Some codebases are faster and safer to rebuild than repair. We begin with an assessment and explain the recommended path before a larger engagement.
Can you finish an incomplete app?
Yes, when the current structure is usable and the remaining requirements are clear. We first define what is missing and agree on a phased scope.
Can you deploy the app after fixing it?
Yes. Deployment support can include environment configuration, production builds, database connectivity and launch on an agreed platform or server.
What do you need before starting?
Usually the repository, setup instructions, error screenshots or logs, current live URL if available, required workflow, environment details and deployment target.
Will you improve security and performance?
Critical issues can be included in the agreed scope. A full security or performance audit is separate from a basic bug-fixing engagement and should be planned explicitly.
Start with an assessment
Have an AI-generated app that is broken, incomplete or difficult to deploy?
Send the tool used, technology stack, repository status, current errors, deployment target, budget range and desired outcome. We will review the information and suggest the next practical step.