AI app for it and development · no coding needed
No-code AI app and agent delivery workspace
Replace several rented builder subscriptions with one owned workspace that turns plain-language requests into deployed, reviewed AI apps and agents.
Made for: Operations and IT teams building internal AI apps and agents without a dedicated engineering team
What it does for you
The problem
Work is spread across several rented no-code agent tools, so workflows, data and approvals do not connect and the business does not own the result.
What it gives you
Deployed, reviewed AI apps and agents
What you give it
Natural-language requestsconnected app datadocumentsrole rules
Build your own version of Blocks, Instruct and more
One app with what these 10 AI tools do, yours to keep and change: Blocks, Instruct, Relay.app Agents, Nimo, Agentplace AI Agents, LemonLime, Albato AI, CREAO, Vybe, AgentX 2.0.
Everything these tools do, in one app
- Natural-language app/agent builder Create apps or agents by describing what you want in plain language, without coding.Found in Blocks, Instruct, Relay.app Agents and 6 more
- Goal-driven autonomous agents Agents plan steps and adapt to conditions to achieve a goal rather than following a fixed checklist.Found in Instruct, Relay.app Agents, Albato AI and 1 more
- Multi-agent collaboration Organize multiple AI agents into teams that work together on tasks.Found in AgentX 2.0
- Visual canvas workflow editor See and edit workflows or agent logic on a visual canvas or flowchart.Found in Instruct, Nimo, Albato AI
- Chat-based builder interface Build and refine agents or apps through a conversational chat interface.Found in Instruct, Agentplace AI Agents
- Built-in agent tools Use built-in tools like web search, SMS, email, and image generation inside agents.Found in Blocks
- Wide app integrations Connect to many external apps and services so agents can read and write data across systems.Found in Blocks, Instruct, Relay.app Agents and 6 more
- Centralized data layer Store and link work information across apps and agents in one place.Found in Blocks
- Custom UI builder Create role-specific interfaces without code.Found in Blocks, Nimo, Vybe
- Template marketplace Start from prebuilt templates and examples to speed up common use cases.Found in Blocks, Agentplace AI Agents, Vybe
- Human-in-the-loop controls Let people review, approve, or refine agent actions for higher-stakes work.Found in Relay.app Agents
- Usage monitoring and controls Track and manage cost and run volume with monitoring and controls.Found in Relay.app Agents
- Local-first storage Keep user outputs and context stored locally, with cloud processing that doesn't persist data for training.Found in Nimo
- Reusable cards and templates Reuse cards and templates to speed up recurring workflows and preserve context.Found in Nimo
- Live preview and testing Test agents or workflows in a live preview with real data before publishing.Found in Agentplace AI Agents, Albato AI
- Developer code access Access and edit the underlying code for custom integrations and advanced control.Found in Agentplace AI Agents, Vybe
- Multiple LLM provider support Connect to multiple large language model providers for flexibility in performance and cost.Found in Agentplace AI Agents, AgentX 2.0
- Sharing and access controls Share agents or apps with teams or external users and restrict access as needed.Found in Agentplace AI Agents, Albato AI, CREAO and 1 more
- Self-learning suggestions Agents learn from usage and regularly suggest improvements or new automations.Found in LemonLime
- Knowledge layer for messy data Organize unstructured data for AI retrieval before passing it to agents.Found in LemonLime
- Per-user specialization Adapt recommendations and behavior to individual roles or users.Found in LemonLime
- Document parsing and extraction Parse and extract data from PDFs and Office files.Found in LemonLime
- Step-by-step testing Run individual automation steps with real data samples to validate and debug.Found in Albato AI
- Secure sharing links Generate secure links to share connections or automations without exposing credentials.Found in Albato AI
- Context-aware copilot per app Each app includes a copilot specialized for its specific workflow.Found in CREAO
- Role-based permissions Manage organizational control with role-based permissions and centralized management.Found in CREAO, Vybe
- Production-ready deployment Deploy apps with built-in authentication, roles, and access controls.Found in Vybe
- Branding and deployment customization Customize branding and deployment, including email and chat interfaces.Found in AgentX 2.0
How it works, step by step
- Build apps and agents from plain-language descriptions
- Run goal-driven agents that plan steps and adapt to conditions
- Organize multiple agents into collaborating teams
- Edit workflows on a visual canvas
- Refine builds through a chat interface
- Use built-in tools such as web search, SMS, email and image generation
- Connect external apps so agents read and write data across systems
- Store and link work information in a centralized data layer
- Create role-specific interfaces without code
- Start from a template marketplace
- Route higher-stakes actions to human review and approval
- Track cost and run volume with usage controls
- Keep outputs and context in local-first storage with non-persistent cloud processing
- Reuse cards and templates across recurring workflows
- Test agents in a live preview with real data before publishing
- Access and edit underlying code for custom integrations
- Connect multiple LLM providers
- Share agents with teams or external users under access controls
- Suggest improvements and new automations from usage
- Organize unstructured data in a knowledge layer for retrieval
- Adapt behavior and recommendations per user role
- Parse and extract data from PDFs and Office files
- Run individual automation steps with real data samples
- Generate secure sharing links without exposing credentials
- Provide a context-aware copilot per app
- Manage role-based permissions centrally
- Deploy with built-in authentication, roles and access controls
- Customize branding and deployment, including email and chat interfaces
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 app and 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 app and 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 links6 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
Replace several rented builder subscriptions with one owned workspace that turns plain-language requests into deployed, reviewed AI apps and agents. For operations and IT teams building internal AI apps and agents without a dedicated engineering team, convert natural-language requests, connected app data, documents and role rules into deployed, reviewed AI apps and agents with human approval and usage controls. The benefit is a testable hypothesis, measured through deployed workflows in production use and reviewer-approved agent actions per delivery hour; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect natural-language requests, connected app data, documents and role rules, then follow this sequence: 1. Build apps and agents from plain-language descriptions. 2. Run goal-driven agents that plan steps and adapt to conditions. 3. Organize multiple agents into collaborating teams. Resolve uncertain cases with qualified reviewers, approve deployed, reviewed AI apps and agents, and measure deployed workflows in production use and reviewer-approved agent actions per delivery hour 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 approved integration set and one deployment environment; final access, data-handling and production decisions remain with the buyer's named owners. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve source attribution, data permissions and access boundaries. Named owners approve substantive changes and deployment scope. One approved integration set and one deployment environment; final access, data-handling and production decisions remain with the buyer's named owners. 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 environment; final access, data-handling and production decisions remain with the buyer's named owners. Implement one approved input format, a bounded representative case set and the first two task modules: build apps and agents from plain-language descriptions; run goal-driven agents that plan steps and adapt to conditions. Support the third module with operator review: organize multiple agents into collaborating teams. 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 app accounts, authorized documents and permitted data sources. Cloud storage, identity providers and deployment 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: Builder chat and canvas, Live preview and step test, Deployment and access. Use a project gallery, a large central canvas with a chat panel for plain-language edits, and a right-hand panel for tools, integrations, knowledge and permissions. Let users compare agent versions side by side. Display draft, in review, approved and deployed states. Provide a secure preview link with comments anchored to the relevant step. Make the task-specific outcome deployed, reviewed AI apps and agents visible beside its evidence, review state and value baseline.
