New release introduces Autonomous Model Generation, Custom Test Cases, and model-driven validation across legacy and modern environments, helping insurance carriers and Insurtechs accelerate delivery and modernization while reducing testing effort, operational risk, and maintenance
Emtech today announced the release of QMT 2.3, a major platform release that advances autonomous software testing through Autonomous Model Generation (AMG), Custom Test Cases, and model-driven validation across legacy and modern enterprise environments.
At the foundation of QMT is Emtech’s patented Deterministic Knowledge Graph technology, which creates a trusted, machine-readable representation of how enterprise applications work. The resulting Digital Blueprint captures screens, workflows, business rules, decisions, data relationships, integrations, and other system behavior, providing a structured foundation for quality engineering, modernization, and system intelligence.
Unlike AI tools that generate isolated test scripts from prompts, QMT follows a model-first approach. AI accelerates application discovery and model creation, while deterministic technology generates repeatable testing and validation from an approved representation of the system. The result is an approach that combines the speed of AI with the governance and repeatability required for enterprise software quality.
QMT 2.3 uses this model to power autonomous testing and validation across complex enterprise environments, including mainframes, modern applications, APIs, databases, integrations, and documents. By bringing these environments into a common model-driven approach, insurance carriers and Insurtechs can accelerate product delivery and modernization, reduce testing and maintenance effort, lower operational risk, and increase confidence in business-critical change.
The Digital Blueprint was originally developed to support systematic test generation, impact analysis, documentation and modernization, while providing a trusted knowledge foundation for enterprise AI. With QMT 2.3, its role expands as carriers and Insurtechs can use the same structured representation to support systematic test generation, impact analysis, documentation, modernization, and provide a trusted knowledge foundation for enterprise AI.
Autonomous Model Generation analyzes applications to identify screens, workflows, business rules, decisions, data relationships, and system dependencies, reducing the manual effort traditionally required to build and maintain application models. AI accelerates application discovery and model creation, while teams can refine and govern the resulting models to create a foundation for repeatable test generation, validation, and system understanding.
Custom Test Cases enables business users, testers, and quality engineers to create precise business scenarios directly from the application model without writing automation scripts. Teams can rapidly create targeted regression, regulatory, customer journey, and defect-reproduction tests while maintaining traceability to the Digital Blueprint and the underlying business processes.
QMT 2.3 extends model-driven testing and validation to legacy and mainframe environments, enabling carriers to bring systems that have traditionally been tested separately into the same Digital Blueprint. Mainframe applications can be modeled and validated alongside modern systems, with support for green-screen interactions including navigation, field input, command entry, cursor positioning, function keys, and screen verification, as well as validation of dynamic terminal content and host responses.
This enables carriers to validate end-to-end business processes across mainframes, web applications, APIs, databases, integrations, and documents. By updating the underlying business model rather than maintaining large collections of individual automation scripts, teams can reduce manual test design and long-term maintenance effort while improving regression coverage.
“Enterprise AI is only as reliable as the knowledge it is built upon,” said Toni Jardini, Chief Innovation Officer at Emtech. “With QMT 2.3, AI helps discover and organize application knowledge, while our patented Deterministic Knowledge Graph technology provides the structure, repeatability, and explainability enterprises need.”
“Carriers have spent decades building complex enterprise systems, yet much of that knowledge remains fragmented across documents, code, and individual experts,” said Alex Rodov, Founder of Emtech. “Our vision extends beyond test automation. We believe enterprise applications need a living Digital Blueprint that helps people understand how those systems work.”
QMT 2.3 is available immediately. Carriers and Insurtechs interested in learning how QMT 2.3 can support software quality, modernization, and enterprise AI initiatives can contact Emtech for a demonstration.
