Quick Start

Navigate to qubitz.ai and click Login.

Enter your email and password. After authentication, you will be redirected to the Project Selection Hub.

From the Project Selection Hub, select the Use Case Tool to discover and identify the right use cases for your projects.

Fill in your business context:

Optionally add a Business Description (up to 2,000 characters) and select your Cloud Provider(s) (AWS, GCP, Azure, Others).

In the Additional Documents section, drag and drop up to 5 files (PDF, DOC, XLS, PPT, images -- max 10 MB each). These help the AI agents understand your business context more deeply.

Select the Deep Analysis button at the bottom right. The analysis modal opens showing a live Connection Log of the multi-agent pipeline. The process takes approximately 6-8 minutes.

You can either:

• Watch live -- Monitor the Connection Log as agents execute research, writing, and publishing phases
• Run in Background -- Click "Run in Background" to close the modal and continue using the platform

When analysis completes, the Results Dashboard appears with:

• Your auto-generated Project ID (e.g., cloud202-461)
• Three report tabs: AI Use Case Discovery, Deep Research, Use Case List
• A two-column grid of generated use case cards with impact badges

Select Go to Project to view the project dashboard.

• Artifacts -- Start here! View your AI-generated artifacts like Use Case Discovery reports and Deep Research documents. You can also chat with the AI to explore new ideas.
• Invite -- Invite collaborators to this session. They can review, rate, and comment on use cases to help you pick the best one.
• Rating -- Rate each use case to help prioritize. Your team's ratings and sentiment analysis determine the ranking order.
• Comment -- Add a comment or view what others have said. Comments feed into sentiment analysis to help rank use cases.

You can also add a custom use case by providing the following details:

Select the Artifacts button to view the generated content and documents:

• AI Use Case Discovery Report -- AI-powered analysis identifying potential use cases and business opportunities from your requirements
• Deep Research Report -- Comprehensive research report with detailed analysis, market insights, and implementation strategies
• Use Case List -- Comprehensive table of AI use cases with business problems, potential solutions, and expected outcomes
• Executive Presentation -- Professional PowerPoint presentation for executive stakeholders with key insights and recommendations
• AWS Architecture Diagram -- Visual representation of AWS infrastructure and services architecture

You can also select the Generate New Artifact button.

Choose the artifact type you want to generate, state the instructions and select Generate.

Select the Chat option to start a conversation with the agent.

Select your finalized use case and click Design App to enter Control Hub. An Application record is created and linked to your jamming session.

Control Hub has 3 tabs: Agentic System, Test Bed, and Deploy. Test Bed and Deploy are disabled until your agents have been deployed at least once.

The AI Architect agent automatically generates a multi-agent architecture based on your use case and research report. Once generated, you can select any agent to understand their configuration.

When you expand an agent card, you can view and edit:

• Name & Description -- Agent identity and role
• Model -- Dropdown with 24 models (Claude, Nova, Llama, Mistral, and more)
• Tools -- RAG, MCP, Web Search, Generate Report, Text to Speech, Speech to Text, Video tools
• Memory -- Short-term, Long-term
• Visibility -- Both, User Only, Admin Only
• System Prompt -- The full agent prompt, editable
• Agent as a Tool -- Which other agents this agent can call

All editable inline, and changes can be saved or refined further via the chat panel.

You can also:

• Refine via chat -- Use the right panel chat to request changes in natural language
• Toggle Platform Agents -- Enable or disable system agents separately from your custom agents

When satisfied with the configuration, click Approve. A Deploy Credentials dialog opens asking for your GitHub username.

The deployment provisions your agentic system on AWS (AgentCore runtime). Deploy logs stream in real-time with a progress bar. On success, the Test Bed and Deploy tabs unlock.

The Test Bed is a live chat environment to test your deployed agentic system.

Type a message to interact with your agents. The Agent Activity Tree on the right panel shows real-time sub-agent orchestration -- each agent's status, tool usage, reasoning, and responses.

After testing, select the Evaluate button to choose up to 8 metrics across multiple dimensions:

Response Quality -- Correctness, Helpfulness, Coherence, Conciseness, Faithfulness, Relevance, Instruction Following, Refusal Detection, Context Relevance

Task Completion -- Goal Success

Tool Usage -- Tool Selection, Tool Parameters

Safety -- Harmfulness, Stereotyping

Once you've selected up to 8 metrics, select the Evaluate button to start the evaluation.

As the evaluation completes, you can review the scores for each selected metric along with detailed explanations and labels for every dimension. Once you're done reviewing, you can navigate to the Deploy tab.

The Deploy tab has two inner tabs: API and Generate App.

API

• API Endpoint -- Your agent's API endpoint URL for external integrations
• API Keys -- Generate and manage keys (max 2 per project). Newly generated keys are shown once -- save them immediately
• Quick Start -- Code example for calling your agent API
• Developer Guide -- Generate developer documentation via the DevGuide agent. Shows versioned list of previously generated guides

Business Case

3 sub-tabs:

• Cost Estimates
  • Monthly MRR, Annual ARR, and Buffer % cards
  • Itemized breakdown of every AWS service with name, description, and monthly cost
  • Three scenario cards: Conservative (0.6x), Base (1x), Growth (2x)
  • Configurable settings: sessions/day, turns/session, buffer %
  • ROI analysis when available

AWS Architecture Diagram -- Renders the architecture diagram for your use case

Export -- Export the business case as PDF. Also includes a link to the AWS Pricing Calculator to verify costs independently.

Generate App

Add optional instructions to guide code generation.

Click Generate App to start. A Brand Kit dialog opens — customize your application name, tagline, primary color, font style, and logo before generating.

The system streams agent thinking, tools used, and file patches in real-time. Generated files appear as expandable cards tagged NEW or MOD with full source code.

After code generation completes, the code is automatically pushed to GitHub and Amplify builds it. On success, a Live Deployment card appears with your live URL.

Move to Prod -- Available once your app is deployed. Moves your application to production and redirects to the Application Management dashboard.