4C Strategies scales testing with AI automation

    4C Strategies overcame massive testing bottlenecks by using QA.tech's AI agents to read dense user manuals and autonomously test highly customized workflows.

    About 4C Strategies

    Company
    4C Strategies
    Industry
    Risk management / Defense / Public sector
    Size
    100–200 employees
    Business Type
    Crisis management & resilience simulation software
    Headquarters
    Sweden (Stockholm)

    Key Use Cases

    Automated E2E UI Testing
    AI-Assisted Test Generation (via PDFs & Manuals)
    Bespoke Customer Environment Verification
    Self-Hosted CI/CD Integration (GitLab)

    The Challenge: complex workflows and highly customized environments

    4C Strategies provides advanced crisis management, risk, and resilience software for the defense and public sectors. Their "Resilience Platform" features a micro-frontend architecture housing distinct products like Risk Manager, Incident Manager, and Continuity Manager.

    Historically, 4C Strategies relied heavily on manual testing, exploratory tests, and rigid BDD (Gherkin/Playwright) scripts. However, this became increasingly difficult to scale due to the highly customizable nature of their software. For major bespoke clients, workflows often differ entirely from the standard General Availability (GA) platform. Maintaining test coverage across multiple concurrent versions, branches, and highly complex UIs with long data dropdowns resulted in a significant testing bottleneck.

    They needed a flexible, deterministic automation tool that could digest their extensive documentation and test myriad custom workflows without breaking at every UI change.

    The Solution: Goal-oriented AI and documentation-driven testing

    After exploring various legacy automation frameworks, the 4C Strategies engineering team partnered with QA.tech to implement an AI-driven approach capable of understanding the intricate context of their software.

    Rapid test generation from dense manuals:

    Due to contractual obligations, 4C Strategies maintains highly detailed, 40-to-50-page PDF user manuals. By feeding these complex documents directly into QA.tech's AI chat, their distributed QA and development teams can rapidly generate relevant, goal-oriented test steps based on a "shared and accepted truth" rather than manual guesswork.

    Navigating Bespoke Customer States:

    QA.tech’s probabilistic AI agent easily navigates 4C's complex visual structure, interpreting dynamically changing dropdowns and tabs that typically break traditional DOM-based tools. It also enables 4C to build test scenarios that interact seamlessly across their different internal products (e.g., verifying that an action in Risk Manager properly updates in Incident Manager).

    Self-hosted GitLab integration:

    To shift testing left, 4C Strategies is connecting QA.tech's API directly into their self-hosted GitLab CI/CD pipelines. This ensures that every new Merge Request is automatically tested by the AI agent on a preview deployment before it merges, keeping their development velocity high.

    The Results: mechanising QA for global defense software

    By shifting from manual checklists to QA.tech’s AI agents, 4C Strategies is building a scalable, automated safety net capable of handling the severe complexity of their defense-grade platform.

    With the ability to automatically generate tests from their existing documentation and deploy them directly into their self-hosted pipelines, 4C Strategies is successfully systematizing their QA process – ensuring top-tier quality for their global clients without the heavy overhead of maintaining manual test execution.

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