AI app for it and development · no coding needed
No-code AI agent delivery workspace
Reduce the time from described task to a monitored, budgeted agent in production.
Made for: Operations and IT teams that need working AI agents but have no dedicated engineering capacity
What it does for you
The problem
Automation needs sit in a queue while teams rent several agent tools that each cover only part of the build, test, deploy and monitor cycle.
What it gives you
Deployed, monitored agent with editable code
What you give it
Plain-language task descriptionssample dataservice credentialsspending limits
Build your own version of Broxi AI, SmythOS and more
One app with what these 10 AI tools do, yours to keep and change: Broxi AI, SmythOS, Vellum, String.com, QuickAgent, Brick Coder AI, Kodey.ai, Cotera, Promptius AI, Alice.
Everything these tools do, in one app
- No-code agent builder Build AI agents without writing code using visual or conversational interfaces.Found in Broxi AI, Vellum, QuickAgent and 3 more
- Natural language agent creation Create agents by describing tasks in plain English or typing prompts.Found in Vellum, String.com, Promptius AI
- Pre-made templates Use ready-made templates that can be customized for specific needs.Found in Broxi AI, Vellum, Cotera
- Instant deployment Deploy agents immediately without manual coding or complex setup.Found in Broxi AI, String.com, QuickAgent and 2 more
- Multiple execution modes Run agents via UI, API triggers, or scheduled runs.Found in Vellum
- Step preview and history Inspect each step an agent will take and review past executions.Found in Vellum
- State management Carry context between runs to support more complex workflows.Found in Vellum
- Wide integration support Connect to many external services and tools.Found in Broxi AI, SmythOS, Vellum and 5 more
- Action-oriented agents Agents perform real actions like sending emails or managing data, not just chat.Found in Kodey.ai
- Embed agents in apps Launch agents inside applications, websites, or dashboards.Found in Kodey.ai
- Budget controls Set spending caps at the agent or task level.Found in Cotera
- Real-time monitoring Track agent behavior with live monitoring and detailed action logs.Found in Cotera
- Editable code output Expose generated code (e.g., Python) for technical users to inspect and modify.Found in Promptius AI, Brick Coder AI
- Built-in IDE and sandbox Test agents locally with scenario triggers and dry runs before deployment.Found in Promptius AI
- Multi-agent workflow support Orchestrate multiple agents with separated responsibilities for multi-step tasks.Found in Promptius AI
- Enterprise-grade security Ensure data protection with enterprise-level security measures.Found in Broxi AI
- Integrated virtual assistant Manage schedules, reminders, and quick data retrieval.Found in SmythOS
- Customizable dashboards Provide real-time insights and analytics through customizable dashboards.Found in SmythOS
- Smart file organization Organize files with AI-based tagging and search functionality.Found in SmythOS
- Context-aware text generation Generate text that adapts to the user's input style and intent.Found in Alice
- Multiple content types Support various content types like articles, blog posts, and social media captions.Found in Alice
- Real-time writing suggestions Provide real-time suggestions and edits to improve grammar and readability.Found in Alice
- Customizable tone settings Allow users to select formal, casual, or professional writing styles.Found in Alice
How it works, step by step
- Build agents from plain-language task descriptions
- Start from pre-made templates and customize them
- Preview each step and review past executions
- Carry context between runs with state management
- Connect external services and tools
- Perform real actions such as sending email or updating records
- Embed agents in apps, sites or dashboards
- Set spending caps per agent or task
- Monitor runs live with detailed action logs
- Expose generated code for inspection and editing
- Test in a built-in sandbox with dry runs
- Orchestrate multiple agents across multi-step tasks
- Generate and revise text in the user's style and tone
- Produce articles, posts and captions as agent output
- Give real-time writing suggestions and edits
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned deployed, monitored agent with editable code 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 agent 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 agent 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 links5 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 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 the time from described task to a monitored, budgeted agent in production. For operations and IT teams without dedicated engineering capacity, convert plain-language task descriptions, sample data, service credentials and spending limits into a deployed, monitored agent with editable code, review states and action logs. The benefit is a testable hypothesis, measured through working agents in production per delivery week and manual hours removed per accepted agent; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect plain-language task descriptions, sample data, service credentials and spending limits, then follow this sequence: 1. Build agents from plain-language task descriptions. 2. Start from pre-made templates and customize them. 3. Preview each step and review past executions. 4. Carry context between runs with state management. 5. Connect external services and tools. 6. Perform real actions such as sending email or updating records. 7. Embed agents in apps, sites or dashboards. 8. Set spending caps per agent or task. 9. Monitor runs live with detailed action logs. 10. Expose generated code for inspection and editing. 11. Test in a built-in sandbox with dry runs. 12. Orchestrate multiple agents across multi-step tasks. 13. Generate and revise text in the user's style and tone. 14. Produce articles, posts and captions as agent output. 15. Give real-time writing suggestions and edits. Resolve uncertain cases with qualified reviewers, approve a deployed, monitored agent with editable code, and measure working agents in production per delivery week and manual hours removed per accepted agent 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 approved integration set and one deployment target; final action authorization and production release remain with the buyer's named owner. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve source attribution, action accuracy and usage permissions. The buyer's named owner approves substantive actions and production scope. One approved integration set and one deployment target; final action authorization and production release remain with the buyer's named owner. 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 action authorization and production release remain with the buyer's named owner. Implement one approved input format, a bounded representative case set and the first two task modules: build agents from plain-language task descriptions; start from pre-made templates and customize them. Support the third module with operator review: preview each step and review past executions. 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 service accounts, authorized sample data and permitted internal systems. Cloud storage, ticketing and messaging destinations. 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: Agent brief and connections, Editable build and test preview, Client run dashboard and delivery. Use a thumbnail gallery for agents, a large central build canvas with step preview, and a right-hand panel for integrations, budgets 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 step. Make the task-specific outcome a deployed, monitored agent with editable code visible beside its evidence, review state and value baseline.
