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Configure AI-driven test case generation

Set up AI-assisted test case generation end-to-end in SquashTM, from configuring the AI server to the first generations performed by your testers.

Required license

AI-driven test case generation is available with a SquashTM Ultimate license 💎.

Why configure generative AI in SquashTM?

Configuring generative AI lets your testers benefit from the following capabilities, directly from any requirement:

  • automatically generate classic test cases (with test steps, prerequisites, importance, reference, and datasets);
  • enrich generation with linked requirements and attached documents;
  • keep editorial control: every suggestion must be validated by the tester before being saved, and remains editable afterwards.

AI is a writing aid

The tester remains responsible for the quality, relevance, and completeness of the generated test cases.

What you will learn

  • Declare an AI server at the instance level (Anthropic, OpenAI, Mistral AI, Azure OpenAI, Google Vertex AI, or a custom server).
  • Prepare a prompt set tailored to your needs.
  • Enable AI on a project by associating it with a server and a prompt set.
  • Verify that the full chain works through a first generation.

Who this guide is for

  • SquashTM administrators: configure the AI server, the prompt set, and enable AI at project level.
  • Project leaders: enable AI on the project when this configuration is delegated to them.
  • Testers: validate the setup through a real generation.

What you need

  • A SquashTM Ultimate 💎 instance.
  • An administrator account for the global steps.
  • A valid API key with one of the supported providers (see the full list in Manage Artificial Intelligence servers).
  • A project containing at least one filled-in requirement to test generation.

Workflow overview

The deployment follows a logical order: each step builds on the previous one, and the last step validates the whole chain.

  1. AI server (global): declared once for the whole instance.
  2. Prompt set (global): reusable across multiple projects.
  3. Project enablement: a project leader or an administrator associates a server and a prompt set with the project.
  4. User-side generation: from a requirement, the tester produces their test cases.

Validation

If the generation at step 4 works, the entire configuration chain is correct. Conversely, if the Generate test cases button is missing on a requirement, one of the steps was likely skipped (see the dedicated section).

Guide structure

  1. Configure the AI server: declare the provider and test the connection.
  2. Prepare a prompt set: use the default prompt sets or create a new one.
  3. Enable AI on a project: link the server and the prompt set to a project.
  4. Generate test cases: first validation generation on the user side.

Each step links back to the corresponding reference page in the documentation for granular details (advanced parameters, Handlebars syntax, per-provider configuration, etc.).

Next step

Configure the AI server.