AI app for operations · no coding needed
Plain-language cross-app automation coordination portal
Reduce manual cross-app coordination while keeping task state, approvals and context in one owned workspace.
Made for: Operations leads and team managers coordinating repetitive cross-app work
What it does for you
The problem
Repetitive cross-app work is rebuilt by hand in several rented tools, and task state, approvals and context are lost between them.
What it gives you
Reviewed AI-driven workflows with persistent state
What you give it
Plain-language task descriptionsconnected app credentialsteam rules
Build your own version of Blimp, Studio Global and more
One app with what these 4 AI tools do, yours to keep and change: Blimp, Studio Global, CodeWords, Hipocampus.
Everything these tools do, in one app
- Natural-language workflow creation Create automations by describing the task in plain English instead of using a complex editor.Found in Blimp, CodeWords
- AI-driven agents Use AI to interpret prompts, transform data, and route work automatically.Found in Blimp, Hipocampus
- No-code builder Set up automations through a visual or guided interface aimed at non-technical users.Found in Blimp
- Chat-based iteration Refine and edit workflows conversationally with an AI assistant.Found in CodeWords
- Code-first workflows Represent automations as readable code for flexibility, portability, and advanced customization.Found in CodeWords
- App integrations Connect multiple apps to pass data and trigger actions automatically.Found in Blimp, CodeWords, Hipocampus
- Built-in testing and debugging Test, debug, and deploy automations directly through the interface.Found in CodeWords
- Ready-to-use templates Start from pre-built templates that can be customized for common automations.Found in CodeWords, Studio Global
- Persistent workflow state Maintain task state and context across time and tools so work continues without losing progress.Found in Hipocampus
- Approvals and delegation Handle approvals, delegation, and escalation workflows tied to specific tasks.Found in Hipocampus
- Task history and context Store notes, summaries, and artifacts outside the model to reduce context loss during handoffs.Found in Hipocampus
- Flexible notifications Surface tasks in team channels or an internal inbox through configurable notification options.Found in Hipocampus
- Pattern learning Learn from observed human actions to take initial passes on repeatable work.Found in Hipocampus
- Collaborative workspace Allow real-time editing and feedback among team members.Found in Studio Global
- Project management tools Track tasks and manage deadlines within the platform.Found in Studio Global
- Data analytics dashboard Measure content performance and engagement through analytics.Found in Studio Global
- AI-assisted content generation Generate text, images, and multimedia elements with AI assistance.Found in Studio Global
- Single-tab workspace Manage all automations from one consolidated interface.Found in Blimp
How it works, step by step
- Create automations from plain-language task descriptions
- Interpret prompts and transform data with AI agents
- Route work automatically between connected apps
- Set up automations through a guided no-code interface
- Refine workflows conversationally with an AI assistant
- Represent automations as readable code for portability
- Connect multiple apps to pass data and trigger actions
- Test, debug and deploy automations in the interface
- Start from ready-to-use templates and customize them
- Maintain task state and context across time and tools
- Handle approvals, delegation and escalation per task
- Store notes, summaries and artifacts outside the model
- Surface tasks in team channels or an internal inbox
- Learn from observed human actions for initial passes
- Support real-time collaborative editing and feedback
- Track tasks and deadlines inside the platform
- Measure run performance and engagement in a dashboard
- Generate text, images and multimedia with AI assistance
- Manage all automations from one consolidated tab
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned reviewed AI-driven workflow 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 Plain-language cross-app automation coordination portal 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 Plain-language cross-app automation coordination portal 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 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 data195 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 manual cross-app coordination while keeping task state, approvals and context in one owned workspace. For operations leads and team managers coordinating repetitive cross-app work, convert plain-language instructions, connected app data and team rules into reviewed AI-driven workflows with persistent state, approvals and task history. The benefit is a testable hypothesis, measured through completed workflow runs per operations hour and manual rework after handoff; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect plain-language task descriptions, connected app credentials and team rules, then follow this sequence: 1. Create automations from plain-language task descriptions. 2. Interpret prompts and transform data with AI agents. 3. Route work automatically between connected apps. 4. Set up automations through a guided no-code interface. 5. Refine workflows conversationally with an AI assistant. 6. Represent automations as readable code for portability. 7. Connect multiple apps to pass data and trigger actions. 8. Test, debug and deploy automations in the interface. 9. Start from ready-to-use templates and customize them. 10. Maintain task state and context across time and tools. 11. Handle approvals, delegation and escalation per task. 12. Store notes, summaries and artifacts outside the model. 13. Surface tasks in team channels or an internal inbox. 14. Learn from observed human actions for initial passes. 15. Support real-time collaborative editing and feedback. 16. Track tasks and deadlines inside the platform. 17. Measure run performance and engagement in a dashboard. 18. Generate text, images and multimedia with AI assistance. 19. Manage all automations from one consolidated tab. Resolve uncertain cases with qualified reviewers, approve reviewed AI-driven workflows with persistent state, and measure completed workflow runs per operations hour and manual rework after handoff 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 fixed app connection set and approved template library; final process decisions and approvals remain human. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve task ownership, source attribution, data accuracy and usage permissions. Operations leads approve substantive changes and deployment scope. One fixed app connection set and approved template library; final process decisions and approvals 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 fixed app connection set and approved template library; final process decisions and approvals remain human. Implement one approved input format, a bounded representative case set and the first two task modules: create automations from plain-language task descriptions; interpret prompts and transform data with AI agents. Support the third module with operator review: route work automatically between connected apps. 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
Client-owned app accounts, authorized task data and permitted team channels. Cloud storage, app connectors and notification 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: Workflow builder and instruction input, Run and approval queue, Task history and analytics. Use a workflow list with status, a central canvas or code view for the selected automation, and a right-hand panel for connected apps, approvals and comments. Let users compare draft and deployed versions side by side. Display draft, testing, awaiting approval and deployed states. Provide a shared team inbox and a client or stakeholder preview link with comments anchored to the relevant run. Make the task-specific outcome reviewed AI-driven workflows with persistent state visible beside its evidence, review state and value baseline.
