AI app for it and development · no coding needed
No-code AI workflow and app delivery workspace
Consolidate the build, run and deployment of AI workflows and apps into one owned workspace.
Made for: Operations and product teams in small and mid-sized companies that need AI workflows and internal apps but have no dedicated engineering capacity
What it does for you
The problem
Workflow and app needs are spread across several rented no-code and AI tools, so data, logic and deployment stay fragmented and the team depends on subscriptions it does not control.
What it gives you
Reviewed, deployable workflow and app package
What you give it
Approved process descriptionsdata sourcesintegration requirements
Build your own version of Glif, AI-Flow and more
One app with what these 10 AI tools do, yours to keep and change: Glif, AI-Flow, AISmartCube, Promptchains, Hyperfeed.ai, Giselle, Zeroqode, Arcktic, Frontly, toolmark.ai.
Everything these tools do, in one app
- No-code visual builder Lets users create workflows or apps by dragging and dropping components without writing code.Found in AI-Flow, Giselle, Zeroqode and 2 more
- AI-powered generation Uses AI to automatically generate content, apps, or task suggestions based on user input or behavior.Found in Glif, AI-Flow, Frontly
- Multi-model integration Allows combining or connecting to multiple AI models and services within one workflow or app.Found in Promptchains, Giselle, toolmark.ai
- Third-party integrations Connects with external applications, APIs, and data sources to extend functionality.Found in AI-Flow, AISmartCube, Promptchains and 2 more
- Conditional logic Enables workflows to branch or take different paths based on previous responses or conditions.Found in Promptchains, Frontly
- Real-time monitoring Provides live tracking and analytics of workflow or task performance as it runs.Found in AI-Flow, Giselle
- Scheduling Allows planning and automating posts or tasks to run at specific times.Found in Glif
- Analytics dashboard Offers insights and performance metrics on posts, workflows, or data through a visual interface.Found in Glif, AISmartCube, Arcktic
- Collaboration tools Facilitates team-based work by allowing sharing, commenting, and managing projects together.Found in Glif, Arcktic
- Data analysis Automates cleaning, processing, and analysis of data to generate insights.Found in AISmartCube, Arcktic
- Template library Provides pre-built templates or blueprints to speed up creation and customization.Found in Glif, Hyperfeed.ai, Zeroqode and 1 more
- Workflow sharing Allows easy sharing of workflows via links so others can run them instantly.Found in Hyperfeed.ai
- Live data integration Incorporates up-to-date external data sources into content generation or workflows.Found in Hyperfeed.ai
- Long-running tasks Supports execution of tasks without explicit time limits, suitable for complex processes.Found in Giselle
- App deployment Enables publishing and deploying created apps to various platforms.Found in Zeroqode
- Embedding Allows AI tools or apps to be embedded into existing websites.Found in toolmark.ai
- Monetization options Provides ways to customize and monetize created AI applications.Found in toolmark.ai
How it works, step by step
- Drag and drop workflow and app components without code
- Generate workflow steps, app screens and task suggestions from a plain description
- Connect multiple AI models and services inside one workflow
- Connect external apps, APIs and data sources
- Branch workflows with conditional logic on prior responses
- Monitor running workflows live with step-level status
- Schedule tasks and posts to run at set times
- Show performance metrics in an analytics dashboard
- Support team sharing, commenting and project roles
- Clean, process and analyze data to produce insights
- Start from a template library of pre-built blueprints
- Share workflows by link so others can run them
- Pull live external data into generation and workflow steps
- Run long-running tasks without explicit time limits
- Deploy apps to chosen platforms
- Embed tools and apps into existing websites
- Set up monetization and access options for published apps
- 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 workflow and app package 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 No-code AI workflow and 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 No-code AI workflow and 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 Cloudflare27 KB
- prompt-vps.mdThe same build on your own server (Docker)27 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria14 KB
- demo/index.htmlThe working demo on sample data200 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
Consolidate the build, run and deployment of AI workflows and apps into one owned workspace. For operations and product teams in small and mid-sized companies that need AI workflows and internal apps but have no dedicated engineering capacity, convert approved process descriptions, data sources and integration requirements into a reviewed, deployable workflow and app package. The benefit is a testable hypothesis, measured through workflows moved from rented tools into the owned workspace and hours of manual work removed per month; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect approved process descriptions, data sources and integration requirements, then follow this sequence: 1. Drag and drop workflow and app components without code. 2. Generate workflow steps, app screens and task suggestions from a plain description. 3. Connect multiple AI models and services inside one workflow. 4. Connect external apps, APIs and data sources. 5. Branch workflows with conditional logic on prior responses. 6. Monitor running workflows live with step-level status. Resolve uncertain cases with qualified reviewers, approve a reviewed, deployable workflow and app package, and measure workflows moved from rented tools into the owned workspace and hours of manual work removed per month against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate workflow steps, app screens and task suggestions 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 approved integration set and one deployment target; final process ownership and production sign-off remain with the buyer. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve process ownership, source attribution, data accuracy and usage permissions. The buyer approves substantive workflow changes and deployment scope. One approved integration set and one deployment target; final process ownership and production sign-off remain with the buyer. 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 approved integration set and one deployment target; final process ownership and production sign-off remain with the buyer. Implement one approved input format, a bounded representative case set and the first two task modules: drag and drop workflow and app components without code; generate workflow steps, app screens and task suggestions from a plain description. Support the third module with operator review: connect multiple AI models and services inside one workflow. 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 process documents, authorized data sources and permitted APIs. Cloud storage, identity and access management, messaging 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: Build canvas, Run and monitor, Deploy and embed. Use a thumbnail gallery for projects, a large central drag-and-drop canvas, and a right-hand panel for components, models, integrations and comments. Let users compare workflow versions side by side. Display draft, in review, running and deployed states. Provide a shareable run link and an embed snippet with comments anchored to the relevant step. Make the task-specific outcome a reviewed, deployable workflow and app package visible beside its evidence, review state and value baseline.
