AI app for it and development · no coding needed
Source-linked app build and automation console
Reduce tool sprawl and manual rebuild work while keeping source-linked control.
Made for: Internal IT teams and operations leads building and automating custom apps and workflows with AI, voice and natural language
What it does for you
The problem
Custom apps and workflow automations are split across rented tools, so context, voice input, execution and self-updating behaviour live in separate subscriptions the buyer does not own.
What it gives you
Reviewed, source-linked app and workflow changes
What you give it
Plain-language requestsvoice inputconnected sourcespermitted screen context
Build your own version of Rehance, Flunkey and more
One app with what these 5 AI tools do, yours to keep and change: Rehance, Flunkey, Rebolt, Zaro, Open Interface.
Everything these tools do, in one app
- Natural language interface Users describe what they want in plain language to build or modify apps and agents.Found in Rebolt, Zaro
- AI-driven text enhancement Suggests improvements in grammar and style for written content.Found in Rehance
- Content clarity tools Helps simplify complex sentences to improve readability.Found in Rehance
- Voice-to-text dictation Converts spoken words into text across applications.Found in Flunkey
- AI question-answering Allows users to ask follow-up questions verbally within the dictation flow.Found in Flunkey
- Context memory Retains information from sessions for later reference.Found in Flunkey
- Action triggers Turns spoken commands into useful tasks beyond just text.Found in Flunkey
- Automated task execution Interprets user commands and executes them via simulated keyboard and mouse inputs.Found in Open Interface
- LLM integration Uses advanced language models to determine necessary actions to achieve objectives.Found in Open Interface
- Self-correction mechanism Uses updated screenshots to course-correct actions and align with desired outcomes.Found in Open Interface
- Cross-platform support Works on multiple operating systems such as MacOS, Linux, and Windows.Found in Open Interface
- Open-source and community-driven Allows inspection and community contributions for continuous development.Found in Flunkey, Open Interface
- Integration with platforms Connects with popular tools like OpenAI, Outlook, OneDrive, SharePoint, Gmail, and Slack.Found in Rebolt, Zaro
- Pre-built capabilities Includes ready-to-use features to accelerate app development.Found in Rebolt
- Automation of business processes Supports automating custom business processes.Found in Rebolt
- User-friendly environment Enables company-wide participation with an easy-to-use interface.Found in Rebolt
- Single-prompt app creation Builds working apps and agents from a single prompt without manual schema definition.Found in Zaro
- Context infrastructure Tracks recency, source, and relationships of data to provide relevant context for agents.Found in Zaro
- Manual context control Allows users to see, scope, and exclude context that Zaro pulls.Found in Zaro
- Self-updating apps Built apps check connected sources daily and refresh themselves automatically.Found in Zaro
- Natural language editing Non-technical users can modify workflows, agents, and apps by describing changes in plain language.Found in Zaro
How it works, step by step
- Accept plain-language build and edit requests
- Suggest grammar and style improvements for written content
- Simplify complex sentences for readability
- Convert spoken words into text across applications
- Answer follow-up questions verbally inside the dictation flow
- Retain session context for later reference
- Turn spoken commands into useful tasks
- Execute interpreted commands through simulated keyboard and mouse inputs
- Use language models to determine actions toward an objective
- Course-correct using updated screenshots
- Run on MacOS, Linux and Windows
- Allow inspection and community contributions
- Connect with OpenAI, Outlook, OneDrive, SharePoint, Gmail and Slack
- Provide pre-built capabilities for faster app development
- Automate custom business processes
- Let non-technical staff modify workflows, agents and apps by describing changes
- Build working apps and agents from a single prompt without manual schema definition
- Track recency, source and relationships of data for agent context
- Let users see, scope and exclude pulled context
- Refresh built apps daily from connected sources
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned reviewed, source-linked app and workflow changes 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 Source-linked app build and automation console 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 Source-linked app build and automation console 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 criteria13 KB
- demo/index.htmlThe working demo on sample data196 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 and manual rebuild work while keeping source-linked control. For internal IT teams and operations leads building and automating custom apps and workflows with AI, voice and natural language, convert plain-language requests, voice input, connected sources and permitted screen context into reviewed, source-linked app and workflow changes. The benefit is a testable hypothesis, measured through accepted app or workflow changes 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 requests, voice input, connected sources and permitted screen context, then follow this sequence: 1. Accept plain-language build and edit requests. 2. Suggest grammar and style improvements for written content. 3. Simplify complex sentences for readability. 4. Convert spoken words into text across applications. 5. Answer follow-up questions verbally inside the dictation flow. 6. Retain session context for later reference. 7. Turn spoken commands into useful tasks. 8. Execute interpreted commands through simulated keyboard and mouse inputs. 9. Use language models to determine actions toward an objective. 10. Course-correct using updated screenshots. 11. Run on MacOS, Linux and Windows. 12. Allow inspection and community contributions. 13. Connect with OpenAI, Outlook, OneDrive, SharePoint, Gmail and Slack. 14. Provide pre-built capabilities for faster app development. 15. Automate custom business processes. 16. Let non-technical staff modify workflows, agents and apps by describing changes. 17. Build working apps and agents from a single prompt without manual schema definition. 18. Track recency, source and relationships of data for agent context. 19. Let users see, scope and exclude pulled context. 20. Refresh built apps daily from connected sources. Resolve uncertain cases with qualified reviewers, approve reviewed, source-linked app and workflow changes, and measure accepted app or workflow changes 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 stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Final architecture, security and production checks remain with qualified IT staff. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve source attribution, permission boundaries and audit trails. Named owners approve substantive changes and deployment scope. One operating system and one connected source set; final architecture, security and production checks remain with qualified IT staff. 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 operating system and one connected source set; final architecture, security and production checks remain with qualified IT staff. Implement one approved input format, a bounded representative case set and the first two task modules: accept plain-language build and edit requests; suggest grammar and style improvements for written content. Support the third module with operator review: simplify complex sentences for readability. 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
OpenAI, Outlook, OneDrive, SharePoint, Gmail and Slack. Cloud asset storage, design-file import/export and publishing 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: Request and context intake, Editable build and automation preview, Review and deployment. Use a thumbnail gallery for apps and workflows, a large central editing canvas, and a right-hand panel for sources, context scope, permissions and comments. Let users compare versions side by side. Display draft, changes requested and approved states. Provide a review link with comments anchored to the relevant step or asset. Make the task-specific outcome reviewed, source-linked app and workflow changes visible beside its evidence, review state and value baseline.
