Project Vision Document

1. Project Overview

Project Name: Build Automated Testing

Project Sponsor: MAD AI

Project Manager: [Project Manager]

Document Version: 1.0

Last Updated: 01/10/2025

2. Vision Statement

Design an automated testing system using MAD AI's cAItalyst AI-as-a-Service product. This system will provide a front-end interface allowing clients to input test cases, which cAItalyst will then execute autonomously to perform comprehensive testing for various projects.

3. Business Objectives

• Develop a user-friendly front-end interface for clients to submit test cases.
• Integrate cAItalyst AI-as-a-Service to automate the execution of test cases.
• Enhance testing efficiency and accuracy for client projects.
• Reduce manual testing efforts and associated costs.

4. Project Scope

In Scope:

• Development of a front-end interface for clients.
• Integration with cAItalyst AI-as-a-Service.
• Automated execution of client-submitted test cases.
• Reporting and feedback mechanism for test results.

Out of Scope:

• Manual testing processes.
• Development of new test cases not provided by clients.
• Maintenance of client-specific test cases outside the automated system.

5. Stakeholders

• Project Sponsor: MAD AI
• Project Manager: [Project Manager]
• Developers: [Developer Names]
• Clients: [Client Names]
• Quality Assurance Team: [QA Team Names]
• Support Team: [Support Team Names]

6. Deliverables

• Front-end interface for test case submission.
• Integrated cAItalyst AI-as-a-Service for automated testing.
• Documentation and user guides.
• Test result reporting system.

7. Assumptions

• Clients will provide well-defined test cases.
• cAItalyst AI-as-a-Service will be compatible with the front-end interface.
• Adequate resources will be available for development and integration.
• Stakeholders will provide timely feedback.

8. Constraints

• Project must be completed within the allocated budget.
• Project timeline is limited to 6 months.
• Compliance with industry standards and regulations.
• Dependence on the existing cAItalyst AI-as-a-Service product capabilities.

9. Risks

• Potential compatibility issues between the front-end interface and cAItalyst.
• Delays in client feedback or test case submissions.
• Resource limitations affecting development timeline.
• Possible need for additional features not initially scoped.