No Rewrite Required · Deployed As-Is · Restore Tested Before Launch · Plain-Language Findings
Take Your AI-Built App From Prototype to Production
You built a working app with Claude Code, Cursor, Lovable or Bolt. We take it to production as it is: managed hosting, monitoring, tested backups and a clear findings report, then ongoing support from one accountable team.
What Does It Mean to Take an AI-Built App to Production?
Taking an AI-built app to production means turning an application generated with tools such as Claude Code, Cursor, Lovable, Bolt or Replit into a service real customers can rely on: securely hosted, monitored, backed up, recoverable and maintained by an accountable team. Codersarts takes your AI-built app to production without rewriting it, by deploying it as it is on a managed server, proving it works under real conditions, and telling you clearly what needs attention.
AI coding tools are excellent at producing working features quickly. They are not responsible for what happens when the app meets real users, real data and real failures. That part is our job.
AI-Built App to Production at a Glance
Question | Answer |
|---|---|
Who it is for | Founders and teams who built an app with AI coding tools and now need it to run reliably |
Tools we work with | Claude Code, Cursor, Lovable, Bolt, Replit, v0, Windsurf, Base44 and similar |
Rewrite required | No; we deploy the app as it is and report what needs fixing |
How it starts | An optional code audit, then the fixed-scope Go-Live package |
How it continues | Managed Run, a monthly retainer for updates, fixes, monitoring and incident response |
Timeline to go live | Usually 5 to 7 business days from secure access handoff |
Starting prices | Go-Live from $2,000; Managed Run from $1,000 per month |
Ownership | You own the code, data, hosting account and backups |
Demo-Ready Is Not Production-Ready
An app that works in a preview window has passed one test: it runs. A production app has to pass many more. The table below shows the difference.
Area | Demo-ready app | Production-ready app |
|---|---|---|
Hosting | Preview URL or a developer's laptop | Managed server or platform sized for real usage |
Configuration | Hardcoded values and localhost URLs | Environment-specific configuration and secure secrets |
Data | Stored wherever the tool put it | Persistent storage that survives restarts and redeploys |
Security | Works for the person who built it | Access checks, input validation and protected keys |
Failures | Someone notices eventually | Monitoring and alerts reach a named person |
Backups | Not considered | Encrypted, offsite and proven by a restore test |
Updates | Never applied | Security and dependency updates on a schedule |
Ownership | The tool or the person who prompted it | An accountable team with defined response times |
Ten Gaps We Find in AI-Built Apps
These are the issues that appear most often when AI-generated code goes live. None of them mean the app is badly built; they mean the app was built for speed, not for operation.
Gap | What happens in production | How we handle it |
|---|---|---|
Hardcoded localhost URLs | Features break as soon as the app runs on a real domain | Move them into environment configuration |
Secrets in the code | API keys leak through the repository or the browser | Move keys into encrypted server-side configuration and recommend rotation |
Missing environment variables | The app starts but key features silently fail | Document and set every required variable |
Data on temporary storage | Uploaded files or local databases vanish after a redeploy | Use persistent storage or a hosted database |
Weak access checks | Users can see or change data that is not theirs | Flag every issue in the findings report with a fix estimate |
No input validation | Forms accept bad or malicious data | Flag and prioritise in the findings report |
No process supervision | One crash takes the app offline until someone restarts it | Supervise every service with automatic restart |
No monitoring | Customers report failures before you know about them | Alerts for uptime, errors, resources, failed jobs and backups |
Unprotected public endpoints | Abuse, spam and surprise AI or email bills | Rate limits and spending caps, with your approval |
No backups | One mistake can lose everything | Encrypted offsite backups and a timed restore test |
The AI Coding Tools We Support
Tool | What it usually produces | What we typically check |
|---|---|---|
Claude Code | Full-stack projects in your own repository, often Node.js, Python or Cloudflare Workers | Secrets handling, environment setup, background jobs and data persistence |
Cursor | Code in your existing stack and repository | Dependency versions, configuration and test coverage |
Lovable | React front ends, often with Supabase for auth and data | Supabase access rules, exposed keys and deployment settings |
Bolt | Full-stack web apps from prompts | Build configuration, database setup and production hosting |
Replit | Apps built and hosted in Replit workspaces | Moving to production hosting, secrets and persistent data |
v0 | Next.js and React interfaces | Integration with a real backend and deployment on Vercel or similar |
Windsurf and Base44 | Full applications generated from prompts | Data model, access control and operational readiness |
If your tool is not listed, we can still help. What matters is the code and the services it depends on, not the tool that wrote it.
Is SQLite Safe in Production?
AI tools often choose SQLite because it needs no setup. Whether that is a problem depends on where the app runs.
On a single managed server with persistent disk, SQLite in WAL mode can be a sound choice for low to moderate traffic, provided it has continuous backups and has been tested through restarts and crashes.
On serverless or ephemeral hosting, a SQLite file stored next to the code can disappear on every deploy, so a hosted database is the safer option.
With multiple app servers, SQLite is not designed for several machines writing at once, so a client-server database is usually needed.
We test your setup during go-live and recommend changes only where the risk is real.
How We Take Your AI-Built App to Production
Step 1: Optional Code Audit
If you want a full security and quality review before launch, start with an AI-Generated Code Audit. It is the right first step when your app handles payments, personal data or customer accounts.
Step 2: Go-Live
We review the code for deployability, set up and secure a managed server, deploy the app exactly as it is, connect monitoring and encrypted backups, and run a full restore test. You receive a test report, a recovery runbook and a findings report with an estimate for every recommended fix. See the Go-Live Package
Step 3: Fix What Matters
You choose which findings to fix and in what order. Approved fixes are charged at $50 per hour based on the report's estimates, so you stay in control of spend.
Step 4: Managed Run
Once the app is live and accepted, our monthly support keeps it secure, updated and monitored, with a named incident owner and defined response times. See Managed Run
Keeping AI Features Under Control
Many AI-built apps also call AI models themselves, to write content, answer questions or process documents. That brings its own operational risks:
Runaway costs. A loop or retry storm can multiply AI provider bills overnight, so we keep or add spending budgets and retry limits.
Model changes. Providers update and retire models, so we monitor for failures and adjust integrations as part of ongoing support.
Silent quality issues. Failed generations can look like successful ones, so we alert on failed jobs, not only on downtime.
Unapproved actions. Sending, publishing and paid generation can stay switched off in a draft-only pilot until you approve them.
Production Readiness Checklist for AI-Built Apps
Use this list to judge where your app stands today. Every item is checked during go-live.
Security
No API keys, passwords or tokens in the code repository or the browser
Every user can only see and change their own data
Forms and APIs validate input before it is stored or used
Public endpoints are rate-limited to prevent abuse
Data
The database lives on persistent storage or a hosted service
Backups are encrypted, stored offsite and proven by a restore
Uploaded files survive restarts and redeploys
Operations
Services restart automatically after a crash or reboot
Errors, failed jobs and full disks trigger alerts to a named person
There is a written way to deploy, roll back and restore
Someone is accountable for applying security updates every month
What Does It Cost to Run an AI-Built App in Production?
Cost component | Who you pay | Typical range for a small app |
|---|---|---|
Hosting | Your cloud provider, at actual cost | A small server or platform plan, often tens of dollars per month |
Database and storage | Your platform provider | Often included in free or entry tiers at low volume |
AI model usage | Your AI provider | Depends on volume and model; controlled by budgets |
Email sending | Your email provider | Often free at low volume |
Go-Live setup | Codersarts | Starting at $2,000, one-time |
Ongoing support | Codersarts | Starting at $1,000 per month |
The go-live measurements give you real numbers for your own app before you commit to monthly support.
What You Receive
Your AI-built app running on a managed server, deployed exactly as it is
Monitoring and alerts routed to a named owner
Encrypted offsite backups, proven with a full restore test
A written test report and recovery runbook
A plain-language findings report with severity, recommendation and cost for each item
An accountable team to keep it running, if you continue with Managed Run
Who This Is For
Non-Technical Founders
You built a working product with AI tools and need an engineering team to make it safe for customers, without learning DevOps yourself.
Technical Founders Short on Time
You can code, but you would rather spend your hours on product and customers than on servers, patches and backups.
Agencies Delivering AI-Built Projects
You build client apps quickly with AI tools and need a dependable partner to run them after delivery. See our white-label app maintenance for agencies.
Pricing
Service | Price | When you need it |
|---|---|---|
AI-Generated Code Audit | Starting at $499 | Before launch, if the app handles payments, personal data or accounts |
Go-Live | Starting at $2,000, one-time | To run the app safely on a managed server |
Fixes from the findings report | $50 per hour, with your approval | To close the gaps you choose |
Managed Run | Starting at $1,000 per month | To keep the app secure, updated and monitored |
24/7 Critical Incident Cover | $250 per month | If the app must be supported at night and at weekends |
Hosting is billed by your cloud provider at actual cost, in an account owned by your company.
What Is Not Included
Rebuilding the app or adding major new features, which we quote separately
Fees for your AI provider, database platform, email provider or hosting
Guarantees about the accuracy or legal compliance of AI-generated content in your app
Switching on live publishing, email or paid AI generation without your written approval
Frequently Asked Questions
Can you put an app built with Lovable, Bolt or Cursor into production?
Yes. We deploy apps built with Claude Code, Cursor, Lovable, Bolt, Replit, v0 and similar tools on a managed server, as they are, with monitoring and tested backups.
Do I need to rebuild my AI-built app first?
Usually not. We deploy it as it is and list anything that needs fixing in a findings report, so you can fix only what matters.
Is AI-generated code safe to run in production?
It can be, once common gaps such as exposed secrets, weak access checks and missing backups are handled. An audit or the go-live findings report shows exactly where your app stands.
How long does it take to go live?
Usually 5 to 7 business days from the secure access handoff.
Can SQLite stay in my app?
On a single managed server with persistent storage and continuous backups, often yes. On serverless hosting or multiple servers, we recommend a hosted database.
What if my app calls AI models?
We keep spending budgets and retry limits in place, monitor failed jobs, and keep paid generation off until you approve it.
Who owns the code and hosting account?
You do. The hosting account is in your company's name and we work through delegated access.
What happens after go-live?
You can continue with Managed Run, so the same team keeps the app secure, updated and monitored every month.
From AI Prototype to Reliable Product
Tell us which tool you used, what the app does and where it runs today. We will recommend the safest path to production and send a clear quote.