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Following are the functional and non-functional requirements that will be implemented in GoTestPro.

2025 - Q1

AI Enhancements: Automated Test Step Creation

  • Deliver AI functionality for automated test step creation.

  • Internal beta by mid-February; public release by late March.

ServiceNow: Core Features (March Deadline)

  • Run Test Cases: Enable test case execution directly within ServiceNow.

  • View Test Cases: Allow users to browse/manage test cases in ServiceNow.

  • View Test Results: Integrate results view into ServiceNow dashboards.

  • AI-Generated Test Cases: Include AI-based suggestions for new test cases.

Internal Milestone:

  • Finalize SAP and Salesforce discovery phases for upcoming initiatives.

2025 - Q2

  • LLM Testing

    • LLM Accuracy Tool: Release a tool to validate LLM responses against expected outputs.

    • LLM Price Tradeoff Tool: Develop a tool comparing performance across LLMs at identical price points. Beta launch by June.

  • SAP Integration: AI for Manual Test Conversion

    • Deliver functionality to convert manual SAP tests into automated AI-driven test steps.

    • Collaborate with pilot customers for real-world validation.

Metrics for Success:

  • Successful beta tests of LLM tools (target: 3 active enterprise users for feedback).

  • Number of manual SAP test cases converted (target: 1,00 cases).

2025 - Q3

Refining AI Features and Salesforce

  • AI Parity Enhancements

    • Collect and implement feedback from Q1 AI test step feature users.

    • Add advanced customization options for AI-generated test cases.

  • Salesforce: Autogenerate Test Cases

    • Launch functionality to create test cases automatically from Salesforce product databases.

    • Include configurable mappings for custom Salesforce environments.

  • LLM Tools Expansion

    • Iterate on LLM accuracy and pricing tools based on Q2 beta feedback.

    • Launch broader marketing campaign targeting AI/LLM-focused customers.

Metrics for Success:

  • Salesforce integration adoption (target: onboard 10 new enterprise users).

  • LLM tools accuracy improvement (target: >90% success rate in testing scenarios).

2025 - Q4

  • AI Parity: Advanced Features

    • Introduce advanced AI algorithms for predictive testing and failure analysis.

    • Develop integrations for additional platforms based on customer demand.

  • LLM Testing Expansion

    • Broaden support for emerging LLMs and optimize performance benchmarking tools.

  • User Feedback and Market Insights

    • Host customer workshops and gather end-of-year feedback for the 2026 roadmap.

Metrics for Success:

  • AI parity feature utilization across platforms (target: 30% increase from Q1).

  • Total revenue growth from new AI and LLM tools (target: 20% YoY increase).

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