Quick Start
Get from zero to a complete AI strategy package in under 25 minutes with Qubitz AI.
Prerequisites
- A modern web browser (Chrome, Firefox, Safari, Edge)
- A valid Qubitz AI account with login credentials
- Basic information about your business: company name, website URL, and a brief description of your operations
Sign In
Navigate to qubitz.ai and click Login in the top-right corner. Enter your email and password. After authentication, your user's avatar (green circle with initial) appears in the navigation bar.
Launch the Use Case Tool
From this page, select the Use Case Tool to discover and identify the right use cases for your projects.

Fill in Your Business Context
Complete the required fields:
| Field | What to Enter |
|---|---|
| Contact Name | Your full name |
| Your work email | |
| Company | Your organization name |
| Country | Select from dropdown |
| Company Website | Your primary website URL (the AI agents will crawl this) |
Optionally add a Business Description (up to 2,000 characters) and select your Cloud Provider(s) (AWS, GCP, Azure, Others).

Upload Supporting Documents (Optional)
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.

Run Deep Analysis
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

Review Your Results
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 Projects 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:
| Field | Description |
|---|---|
| Title | Name of your use case |
| Description | Description of the use case |
| Business Value | Low, Medium, or High |
| Implementation Timeline | 1-3 months, 4-6 months, 7-12 months, or 12+ months |
| Estimated ROI | Low, Medium, or High |

Generate Additional Artifacts
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.

AI Assessment
The AI Assessment page is a standalone two-panel layout for running AI readiness assessments on any company.
Left Panel
- Previous Companies -- Dropdown listing all companies you've assessed before. Selecting one loads its assessment history.
- New Company -- Enter Company Name (required), Company Website (required), and Description (optional) to start a fresh assessment.
- Start Assessment -- Opens the AI Readiness assessment modal.
- Assessment Reports -- 6 report types, each expandable with versioned PDFs:
- Revised Priority Use Cases
- Platform Decision (AgentCore vs Amazon Q)
- Gap Mitigation Plan
- AWS Fit Feasibility Report
- ROI Modeling Report
- Well-Architected Framework Review
Right Panel
PDF viewer when a report is selected, or an empty state prompting you to select a report.

AI Readiness Assessment
A 10-20 question adaptive assessment tailored to your company. Questions are generated in real-time around your specific goal or challenge, with AI-prefilled suggestions you can edit. The assessment covers 6 categories:
- Organization & Strategy
- Tech Infrastructure
- Data Readiness
- Team & Skills
- Compliance
- AI Initiatives
On completion, 6 scored reports are generated based on your responses. You can also upload supporting documents before submitting (Current State Architecture, Compliance Policies, IT Roadmap, Legacy System Docs, Vendor Contracts) to enrich the assessment. Your assessment answers are also used as verified context when generating other reports and analyses.

Control Hub
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. It may ask clarifying questions before generating the spec. 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 and Bedrock API key. You can validate your Bedrock API key before proceeding with the deployment.

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.

Test Bed
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.

Deploy
The Deploy tab has two inner tabs: Generate App and API.
Generate App
Add optional instructions to guide code generation.

Click Generate App to start -- 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. This typically takes 3-5 minutes.

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.

After a successful deployment, Update Your Application (App Refiner) becomes available:
- Describe the changes you want in plain English with live preview
- Once you have made the updates, select the Deploy Changes button
- Changes will be live in approximately 9-10 minutes at the same live URL

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.

Move to Prod -- Available once your app is deployed. Moves your application to production and redirects to the Application Management dashboard.
Application Management
When you click Move to Prod, you're redirected to the Application Management dashboard with 7 tabs:
1. Overview
- App name, description, deployed URL, and GitHub repo link
- Generate documents:
- AWS WAFR Report -- Evaluates your project against AWS best practices across operational excellence, security, reliability, performance, and cost optimization pillars
- Application Design Document -- Comprehensive design document covering your project's architecture, data models, API contracts, and implementation details. Useful for onboarding and technical reviews
- View previously generated documents with download links and timestamps

2. Agents
- User Agents -- Expandable cards for each custom agent. Edit model (24 options), tools, memory, IAM policy, and system prompt
- Platform Agents -- System agents that can be toggled on/off but are not editable

3. App Config
- Configure GitHub collaborator and Bedrock API key
- Manage custom domains with DNS records and SSL verification
- API endpoint, API keys (max 2), Quick Start code, and Developer Guide
- Build history with all versions, statuses, and deployed URLs
- Fix with Refiner -- Available when a build fails, auto-fixes the issue
- App Refiner -- Make changes to your deployed app in plain English

4. Test Bed
- Live chat with your deployed agents
- Agent Activity Tree for real-time sub-agent orchestration
- Run evaluations across up to 8 metrics

5. Observability
- Key metrics: Total Sessions, New Sessions, Total Traces, Average Latency, Error Rate
- Token Usage by Model, Resource Consumption, Error Breakdown
- Agent Spans with trace count, error count, and average latency
- Click any session to expand the Trace Detail Panel

6. FinOps
- Period selector: This Month, Last 7 Days, Today
- Summary cards: Total cost, number of services, daily average
- Cost Breakdown by Service with itemized AWS costs
- Daily Cost Trend showing spending per day
- Cost data may take up to 24 hours to appear after deployment

7. Settings
- Application configuration: Application ID, Environment, Region
- Access control: User permissions and team roles
- Danger Zone -- Teardown Application to permanently delete all associated AWS resources (requires typing "delete" to confirm)
