Live Webinar, Thursday, July 28th 2026

10-10:45 AM CEST

Release faster. Test smarter. How AI cuts the effort in your quality assurance

Starting point: The challenges in quality assurance
In today’s software development, companies are under enormous pressure to deliver releases faster and more reliably. Yet reality often looks different:

• Inconsistent and unclear requirements documentation makes test planning difficult.
• Automated test case creation often remains wishful thinking – manual processes dominate.
• A lack of qualified Subject Matter Experts (SMEs) leads to knowledge gaps.
• Low test coverage due to limited resources and time.
• Slow test cycles delay releases and increase risk.
• Fragmented tool and data landscapes prevent a holistic QA approach.
• Rising regulatory requirements such as GDPR and the EU AI Act increase the documentation and audit effort.
• The shortage of skilled QA professionals makes the situation even worse.

The solution: msg.TestCaseGen – your AI assistant for quality assurance
msg.TestCaseGen.ai is an AI assistant with a consistent human-in-the-loop approach: the AI suggests, the human decides. Four modular building blocks cover the entire testing process:

• Requirements analysis & process creation: AI extracts, structures and consolidates requirements from Word, PDF, Confluence and Jira – including automatic checks for completeness, consistency and contradictions, as well as automatic BPMN process visualisation.
• Test case analysis & creation: Automated generation of complete, structured test cases based on established test design techniques (equivalence partitioning, boundary values, decision tables) – with coverage analysis, risk-based prioritisation and duplicate avoidance.
• Test data generation: Synthetic, GDPR-compliant test data – without productive personal data.
• Quality Engineering Orchestration: Seamless integration into existing tool chains (Jira/Xray, Azure DevOps, Tricentis, CI/CD) via the Model Context Protocol (MCP).

End-to-end traceability from requirement to test case makes every decision audit-proof and verifiable – including compliance documentation in line with the EU AI Act. On request, it can be operated fully on-premise and with open language models: digital sovereignty without vendor lock-in.

The results are measurable: in real-world projects, the effort for requirements analysis and test case creation each drops by around 60 %, and for coverage analysis by up to 95 % – from 6 weeks down to 2 weeks overall (66 % savings).

Key Learnings:

• How to cut the effort in quality assurance by up to 66 % with msg.TestCaseGen.ai – from requirements analysis to test coverage
• How AI detects gaps, contradictions and ambiguities in requirements before they turn into costly defects
• How to achieve higher test coverage even under resource constraints – with human-in-the-loop: the AI suggests, the human decides
• How end-to-end traceability and EU AI Act-compliant documentation create regulatory certainty (GDPR, auditability)
• How the AI assistant integrates into your existing tool chain (Jira, Azure DevOps, CI/CD) – on request operated fully on-premise and sovereign

PARTNER

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