AI app for it and development · no coding needed
Chat-built full-stack app delivery workspace
Reduce tool sprawl while keeping the generated app and its source under the team's control.
Made for: Small product teams and internal builders shipping full-stack web apps
What it does for you
The problem
Building, hosting and iterating a full-stack app requires stitching together separate coding, database, hosting and deployment tools.
What it gives you
A running, source-accessible full-stack app with a live link
What you give it
Chat instructionsproject conventionsdeployment constraints
Build your own version of AppWizzy, JDoodle.ai MCP and more
One app with what these 4 AI tools do, yours to keep and change: AppWizzy, JDoodle.ai MCP, Orchids, Steamship.
Everything these tools do, in one app
- Chat-driven app building Lets users create and modify apps by talking to an AI assistant in chat.Found in AppWizzy, JDoodle.ai MCP, Orchids
- Full-stack code generation Generates frontend, backend, database, authentication, and payments code for an app.Found in Orchids
- Built-in database Provides persistent storage for app data without adding a separate database service.Found in JDoodle.ai MCP, Orchids, AppWizzy
- Built-in hosting Deploys and runs the app so it can be used online.Found in JDoodle.ai MCP, Orchids, AppWizzy and 1 more
- Live preview Shows changes to the app in real time while editing.Found in JDoodle.ai MCP
- One-step publishing Publishes the project to a live link in a single step.Found in JDoodle.ai MCP
- Source code access Gives users direct access to the generated source code.Found in AppWizzy
- Persistent versioned workspace Keeps files, diffs, Git/checkpoints, logs, and build state for recovery and iteration tracking.Found in AppWizzy
- In-environment build and run Builds and runs the app in the same environment where it was created instead of exporting it elsewhere.Found in AppWizzy
- Private dedicated VM Provides a private virtual machine with an AI coding agent preinstalled.Found in AppWizzy
- Next.js project output Produces projects that follow Next.js conventions for routing and state handling.Found in Orchids
- High-fidelity UI reproduction Generates accurate interfaces and can synchronize media in many cases.Found in Orchids
- Built-in authentication and payments Includes auth and payment flows in generated apps without third-party integrations.Found in Orchids
- Free automatic bug fixes Applies certain fixes without consuming credits during iteration.Found in JDoodle.ai MCP
- Managed cloud hosting Hosts applications in the cloud with logging, key management, and data storage.Found in Steamship
- Flask-style endpoints Wraps code with minimal changes into live, multi-user APIs.Found in Steamship
- Async compute and embedding search Provides asynchronous compute and embedding search for AI applications.Found in Steamship
- Pre-integrated AI swap-ins Offers out-of-the-box support for components such as OpenAI, memory variants, Google Search, and audio transcription.Found in Steamship
How it works, step by step
- Create and modify apps through chat
- Generate frontend, backend, database, authentication and payments code
- Store app data in a built-in database
- Deploy and run the app on built-in hosting
- Show a live preview while editing
- Publish to a live link in one step
- Expose the generated source code
- Keep a persistent versioned workspace with files, diffs, checkpoints and logs
- Build and run the app in the same environment
- Provide a private dedicated VM with the coding agent preinstalled
- Produce Next.js projects following routing and state conventions
- Reproduce high-fidelity interfaces and synchronize media where supported
- Include authentication and payment flows without third-party integrations
- Apply certain bug fixes automatically during iteration
- Host in the cloud with logging, key management and data storage
- Wrap code into live multi-user API endpoints
- Provide asynchronous compute and embedding search
- Offer pre-integrated AI components such as model, memory, search and transcription
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned running, source-accessible full-stack app with a live link 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 Chat-built full-stack app delivery 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 Chat-built full-stack app delivery 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 links4 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare25 KB
- prompt-vps.mdThe same build on your own server (Docker)25 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria12 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 tool sprawl while keeping the generated app and its source under the team's control. For small product teams and internal builders shipping full-stack web apps, convert chat instructions, project conventions and deployment constraints into a running, source-accessible full-stack app with a live link. The benefit is a testable hypothesis, measured through accepted app changes per delivery hour and rework after publishing; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect chat instructions, project conventions and deployment constraints, then follow this sequence: 1. Create and modify apps through chat. 2. Generate frontend, backend, database, authentication and payments code. 3. Store app data in a built-in database. 4. Deploy and run the app on built-in hosting. 5. Show a live preview while editing. 6. Publish to a live link in one step. Resolve uncertain cases with qualified reviewers, approve a running, source-accessible full-stack app with a live link, and measure accepted app changes per delivery hour and rework after publishing against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the 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 supported framework version and one deployment target; security review and production release remain human. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve source ownership, dependency licenses, secret handling and deployment permissions. Named owners approve production releases and external actions. One supported framework version and one deployment target; security review and production release remain human. 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 supported framework version and one deployment target; security review and production release remain human. Implement one approved input format, a bounded representative case set and the first two task modules: create and modify apps through chat; generate frontend, backend, database, authentication and payments code. Support the third module with operator review: store app data in a built-in database. 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
Team-owned repositories, authorized design files and permitted data sources. Cloud hosting, source control, CI and deployment destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Chat build workspace, Editable code and preview, Deployment and operations. Use a project list with environment status, a central chat and editor canvas, and a right-hand panel for files, diffs, logs and settings. Let users compare versions side by side. Display draft, building, running and published states. Provide a client preview link with comments anchored to the relevant screen. Make the task-specific outcome a running, source-accessible full-stack app with a live link visible beside its evidence, review state and value baseline.
