Understanding Testing Modes

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Overview

ratl.ai provides two distinct modes to help teams optimize their software testing workflows:

1. Assisted Mode – Ideal for modular testing where users have full control.

2. Autonomous Mode – Designed for end-to-end automation with minimal manual setup.

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Assisted Mode

Use Case: Best for QA teams and developers who want to test APIs, Web apps, Load, and Performance as separate tasks.

Setup Flow

1. Mode Selection User selects "Assisted Mode" from the initial screen.

2. Workspace Setup(if first user to the organisation)

   • Name the workspace

   • Define organization URL

   • (Optional) Add a workspace description

   • Enable auto-join for users with a specific domain email

3. Workspace Discovery

   • Shows existing workspaces within the org

   • Option to join or create a new one

4. Team Invitation

• Invite teammates by entering email addresses

• Option to skip this step

1. User Role Setup

   • Enter user name

   • Choose from roles: QA, Developer, Product Manager, Tech Lead, CXO, Designer, DevOps, TechOps, SiteOps, Other

2. Test Type Selection Final step before reaching the dashboard. Choose from:

   • API Functional Testing

   • API Integration (E2E) Testing

   • Load & Performance Testing

   • Web Application Testing

Once a test type is selected, the user is directed to the dashboard to begin testing.

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Autonomous Mode

Use Case: Built for teams that prefer a hands-off, intelligent testing flow using context-driven automation.

Setup Flow

1. Mode Selection User selects "Autonomous Mode" from the initial screen.

2. Workspace Setup Same as Assisted Mode (workspace name, org URL, invite team, join existing workspace, and set user role).

3. SDLC Context Collection The user selects relevant tools and practices from their software development lifecycle (SDLC). Each selected item contributes to a projected context score:

   • Requirements / User Stories Tools like JIRA, ClickUp, Notion

   • Design/UX Artifacts Tools like Figma, Miro, Whimsical

   • API Documentation Tools like Swagger, Postman, Stoplight, Insomnia

   • Code Repository Tools like GitHub, GitLab, Bitbucket

   • Code Quality / Static Analysis Tools like SonarQube, ESLint, Codacy

   • AI Code Assistants Tools like GitHub Copilot, Cursor, TabNine, CodeWhisperer

   • CI/CD Tools like Jenkins, GitHub Actions, CircleCI

   • Analytics Tools Tools like GA, Mixpanel, Heap, Amplitude

   • Test Environment Tools like Docker, Kubernetes

   • Monitoring & APM Tools like New Relic, Datadog, Prometheus, Sentry

4. Platform Integration The user further integrates their tool stack by selecting platforms used across project management, testing, collaboration, and environments.

5. Context Score Assessment User receives a Projected Context Score (0–100) based on SDLC coverage and tool integrations. Score factors include:

   • Test Planning

   • Code Quality

   • API Documentation

   • CICD Context & Readiness

   • Test Environment Context

   Each section is scored to help identify gaps and optimize automation readiness.

End of Setup

After the context score is shown, users are ready to go autonomous and will be directed to the dashboard.

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Summary of Differences

Feature	Assisted Mode	Autonomous Mode
Control	Manual test selection	Fully automated testing flow
Integration Required	Minimal	Extensive (SDLC-wide)
Best For	Modular, focused testing	Holistic, continuous testing
Setup Depth	4 steps	Up to 6 steps including integrations and scoring
Outcome	Manual dashboard launch	Auto-generated test strategy & dashboard

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For more, visit: Learn more about Assisted and Autonomous Modes (as shown in the UI).