A Local-First QA Workspace for Web UI & API Testing —
Built for Teams With or Without AI

If I run WebSureQTool on 50 CI/CD agents, do I need 50 Pro licenses?

No. Pro seats apply to the people who author, review, and maintain your suites — not the machines that execute them. WebSureQTool runs headless from the command line with no per-machine licensing, so CI/CD runners, containers, and VMs execute suites freely. Whether you run on 10, 100, or 1,000 agents, your plan counts your quality engineers, not your infrastructure.

Is WebSureQTool only for small teams, or can enterprises use it at scale?

There is no team-size limitation — WebSureQTool serves a solo tester the same way it serves an enterprise QA organization. Pro licensing counts only the people who author, review, and maintain suites; execution is unlimited, so any number of CI/CD agents, containers, and VMs can run your work with no per-machine licensing. And because suites are readable YAML/JSON files, large teams version, review, and share them through the same Git workflows they already use.

For enterprises with specific requirements, SoftTelRG also offers source-code licensing by agreement — available on short notice and scoped to your needs — alongside QA consulting and custom development from the same team that builds the product. Exported Java/JUnit and C#/NUnit Selenium code carries no dependency on WSQ, so enterprise teams can standardize on their own infrastructure at any scale.

Does WebSureQTool meet enterprise governance requirements — access control, approvals, audit trails, and traceability?

Yes — through a deliberate architectural choice. WebSureQTool is an automation workspace, not a monolithic test-governance platform, and that is exactly what makes governance work: because every artifact is a plain file (suite.yaml, CSV/JSON datasets, run.json, junit.xml, HTML reports), governance runs through the enterprise systems you already trust and have already audited. Role-based access and segregation of duties come from your repository permissions; formal review and approval from pull requests and branch protection; an immutable change history from Git itself; and requirement-to-test-to-execution traceability from linking suites and run artifacts to requirement IDs in Jira, Azure DevOps, or your ALM. Nothing lives in a proprietary database — an auditor can open and read every test, every dataset, and every result.

For regulated environments: the app runs within an offline grace period between entitlement checks, update checks can be turned off entirely, and a Security Summary for Procurement (PDF), data-flow documentation, and a data-processing agreement are available for security review — see /security. Requirements beyond the public feature inventory, such as long-term offline operation in restricted networks or organization-specific compliance workflows, are addressed through enterprise source-code licensing and custom development from SoftTelRG, scoped by agreement on short notice.

And if your organization requires governing features like centralized reporting or a formal approval process as built capabilities — rather than through your own Git and ALM stack — SoftTelRG can deliver them within short notice under an enterprise agreement, implemented to your hosting preference (cloud, on-premises, or restricted network), your data-source security requirements, and your repository and integration preferences. The file-based architecture is the foundation, not the ceiling.

Can I use ChatGPT, Claude, or Copilot to write tests for WebSureQTool?

Absolutely — and this is exactly how WSQ fits into sovereign, AI-assisted testing. WebSureQTool uses YAML for Web UI suites and JSON for API tests, formats modern LLMs generate naturally. Describe your scenario, let your assistant draft selectors, steps, flows, or API calls, paste the output into the Suite Editor, and WSQ executes it deterministically and produces full evidence (HTML, JUnit XML, run.json). AI drafts; WSQ runs, logs, and proves. You get AI speed with human-verified auditability.

How does WSQ handle dynamic test data (unique emails, timestamps) to prevent collisions in parallel runs?

WebSureQTool resolves variables inline using ${...} or {{...}} and injects fresh values per run — including ${random6}, ${nowEpochMs}, ${timestamp}, ${environment}, ${browser}, and ${baseUrl}. You combine these into unique fields (e.g., user_${random6}_${nowEpochMs}@example.test). For table-driven tests, bind a CSV/JSON dataset with datasetRef and use ${item} / ${itemIndex}. In load mode (--load-users, --load-iterations), each concurrent session regenerates its own random and timestamp values, so parallel runs get distinct data instead of colliding on hard-coded values. All data generation happens locally, with no external faker APIs or cloud services.

Does WebSureQTool support visual regression or screenshot comparison?

WSQ captures screenshots automatically where they matter for triage: on any failure and at the end of every run, with the first failing step's screenshot pinned in the HTML report. What WSQ deliberately does not include is a proprietary pixel-diff engine. Instead, WSQ exports standard Selenium Java/C# code, so you can plug in your preferred visual regression tools — Pixelmatch, OpenCV, Percy, or any library already in your pipeline — and run them alongside WSQ's deterministic functional and performance assertions. You get visual diffing your way, without being locked into ours.