AI app for it and development · no coding needed
Prompt-to-app build and deployment workspace
Reduce toolchain assembly while keeping the generated code and deployment under the buyer's control.
Made for: Small software teams and internal product owners who need working web applications without assembling a separate toolchain
What it does for you
The problem
Plain-language app descriptions are scattered across several rented tools for generation, hosting, editing, debugging and deployment, so code, data and deployment control stay outside the buyer's business.
What it gives you
A reviewed, deployable web application the buyer owns
What you give it
Plain-language app descriptionsexisting codebasestemplatesintegration requirements
Build your own version of Lazy AI, Meku and more
One app with what these 10 AI tools do, yours to keep and change: Lazy AI, Meku, gptengineer.app, Databutton, co.dev, LaraCopilot, Pythagora 2.0, Bolt.new, mern.ai, LlamaCoder.
Everything these tools do, in one app
- Prompt-to-app generation Creates a working web application from a plain-language description of what you want.Found in Meku, gptengineer.app, Databutton and 6 more
- Full-stack code output Produces both frontend and backend code, including the data layer, for the app.Found in Meku, Databutton, co.dev and 4 more
- Built-in hosting and deployment Publishes the finished app online without needing separate hosting setup.Found in Meku, gptengineer.app, Databutton and 5 more
- Custom domain support Lets the deployed app run on your own domain name.Found in Meku, Databutton, co.dev
- Iterative refinement by chat Lets you adjust and improve the app through further plain-language commands.Found in gptengineer.app, Databutton, co.dev and 2 more
- Live preview Shows the running app so you can see changes as they happen.Found in gptengineer.app, mern.ai
- In-browser editing Lets you edit the generated code directly in the browser without a local setup.Found in Bolt.new, mern.ai
- Code export and ownership Gives you the generated source code to keep, download, or host elsewhere.Found in LaraCopilot, co.dev, mern.ai
- Git integration Connects the generated project to Git so developers can contribute code alongside the AI.Found in gptengineer.app, LaraCopilot
- Ready-made templates Provides starter templates you can remix to speed up building common app types.Found in Meku, Lazy AI
- External API and database integration Connects the app to outside services, APIs, and databases.Found in Databutton, co.dev, Meku
- Integrated debugging tools Helps find and fix problems with breakpoints, logs, database inspection, or AI-suggested fixes.Found in Pythagora 2.0, co.dev
- Team collaboration Lets multiple people work on the same project with roles and shared access.Found in LaraCopilot, Databutton
- Frontend framework choice Lets you pick which frontend technology the generated app uses.Found in LaraCopilot
- Multi-language prompts Accepts app descriptions written in languages other than English.Found in LaraCopilot
- Import existing projects Brings an existing codebase into the tool to refactor or extend it.Found in LaraCopilot
- One-click rollback Reverts a deployment instantly if something goes wrong.Found in LaraCopilot
- Content generation Writes text such as articles, emails, and social media posts.Found in Lazy AI
How it works, step by step
- Generate a working web application from a plain-language description
- Produce frontend and backend code including the data layer
- Publish the finished app online without separate hosting setup
- Support custom domain names
- Refine the app through further plain-language commands
- Show a live preview of the running app
- Edit generated code in the browser without local setup
- Export source code for download or external hosting
- Connect the project to Git for developer contributions
- Provide starter templates for common app types
- Connect external APIs and databases
- Offer debugging tools with logs, database inspection and suggested fixes
- Support team collaboration with roles and shared access
- Let users choose the frontend framework
- Accept app descriptions in languages other than English
- Import existing codebases to refactor or extend
- Revert a deployment with one click
- Generate text such as articles, emails and social media posts
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned reviewed, deployable web application the buyer owns with source references and unresolved questions
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Prompt-to-app build and deployment workspace with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Prompt-to-app build and deployment workspace with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links5 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare26 KB
- prompt-vps.mdThe same build on your own server (Docker)26 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria13 KB
- demo/index.htmlThe working demo on sample data201 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Reduce toolchain assembly while keeping the generated code and deployment under the buyer's control. For small software teams and internal product owners who need working web applications without assembling a separate toolchain, convert plain-language app descriptions, existing codebases, templates and integration requirements into a reviewed, deployable web application the buyer owns. The benefit is a testable hypothesis, measured through accepted working applications per build hour and corrections after deployment; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect plain-language app descriptions, existing codebases, templates and integration requirements, then follow this sequence: 1. Generate a working web application from a plain-language description. 2. Produce frontend and backend code including the data layer. 3. Publish the finished app online without separate hosting setup. Resolve uncertain cases with qualified reviewers, approve a reviewed, deployable web application the buyer owns, and measure accepted working applications per build hour and corrections after deployment against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One fixed deployment target and approved integration set; final security, data-handling and production-readiness checks remain with qualified engineers. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve source attribution, license compliance and usage permissions. Buyers approve substantive changes and deployment scope. One fixed deployment target and approved integration set; final security, data-handling and production-readiness checks remain with qualified engineers. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One fixed deployment target and approved integration set; final security, data-handling and production-readiness checks remain with qualified engineers. Implement one approved input format, a bounded representative case set and the first two task modules: generate a working web application from a plain-language description; produce frontend and backend code including the data layer. Support the third module with operator review: publish the finished app online without separate hosting setup. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Buyer-owned repositories, authorized codebases and permitted data sources. Cloud hosting, Git providers, external APIs and databases. Start with file exchange and validate destination specifications before promising direct deployment. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Project brief and inputs, Editable build preview, Review and deployment. Use a thumbnail gallery for projects, a large central editing canvas, and a right-hand panel for prompts, files, integrations and comments. Let users compare versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant screen or file. Make the task-specific outcome a reviewed, deployable web application the buyer owns visible beside its evidence, review state and value baseline.
