Emtech Unveils QMT 2.3 for Enhanced Software Testing in Insurance Sector
Emtech has announced the launch of QMT 2.3, a cutting-edge iteration of its software testing platform tailored for insurance carriers and InsurTechs.
This upgraded version introduces features such as Autonomous Model Generation, Custom Test Cases, and model-driven validation, which seamlessly integrate both legacy and modern enterprise systems.
At the core of QMT is Emtech’s innovative Deterministic Knowledge Graph technology. This advanced system constructs a machine-readable framework of enterprise applications, referred to by Emtech as a Digital Blueprint.
The Digital Blueprint encompasses a comprehensive mapping of screens, workflows, and business rules pertinent to an application. Moreover, it meticulously documents data relationships, decision-making processes, integrations, and various behaviors demonstrated during testing and validation.
Unlike traditional automation approaches that derive individual scripts directly from AI prompts, QMT employs a model-first testing methodology.
While AI aids in application discovery and model fabrication, it is the deterministic processes that yield reproducible tests grounded in an authorized system model.
The QMT 2.3 architecture is applicable to both mainframes and contemporary applications, and it proficiently handles APIs, databases, system integrations, and documentation all within a cohesive testing environment.
Emtech asserts that insurance firms can leverage this platform throughout software development and modernization initiatives.
This model is designed to alleviate the burden of manual testing endeavors and minimize the upkeep associated with extensive collections of individual automation scripts.
The feature of Autonomous Model Generation adeptly analyzes applications to automatically recognize screens and workflows.
It further identifies business rules, decisions, data connections, and system interdependencies prior to establishing a preliminary application model.
Post-generation, teams have the opportunity to review and refine these models. The sanctioned model subsequently serves as the foundation for the creation of tests, validation processes, and documentation.
The newly integrated Custom Test Cases functionality empowers business users, testers, and quality engineers to formulate scenarios directly from the application model, eliminating the need to draft separate automation scripts for each scenario.
These tests encompass various types, including regression testing, compliance with regulatory standards, customer journey assessments, and defect resolution.
Importantly, test cases remain intrinsically linked to the Digital Blueprint and the business processes encapsulated within the model.
Additionally, QMT 2.3 extends its model-driven testing capabilities to mainframe systems. This allows insurers to include both legacy applications and more recent systems within a single Digital Blueprint, removing the necessity for disparate testing frameworks.
Mainframe support features comprehensive navigation through green screens, input fields, and commands.
The platform manages cursor placement, function key operations, screen verification, and validation of dynamic terminal content and host responses.
This integrative approach enables insurers to examine business processes that span multiple technology environments. A singular workflow may encompass a mainframe application, web interface, and API, followed by validations in databases or documents.
Emtech elucidates that modifications can be applied to the foundational business model rather than requiring updates to a plethora of automation scripts individually.
The firm anticipates that this structural innovation will diminish long-term maintenance efforts while amplifying the breadth of regression testing.
The Digital Blueprint, initially conceived for test generation, impact assessment, and system documentation, has now been positioned as a vital reservoir of structured application knowledge beneficial for modernization initiatives and enterprise AI systems.
Reliability in enterprise AI is fundamentally contingent upon the quality of the knowledge it is predicated on. While AI facilitates the discovery and organization of application information, the Deterministic Knowledge Graph delivers a systematic foundation for consistent validation.
Toni Jardini, Chief Innovation Officer at Emtech
Emtech’s founder, Alex Rodov, remarked on the fragmented nature of application knowledge within large enterprises, which often resides across source code, various documents, and individual employees.
He shared the company’s longer-term vision: to curate a continuously evolving Digital Blueprint that accurately reflects the operational landscape of these systems.
QMT 2.3 is available for immediate deployment, with Emtech strategically targeting insurance carriers and InsurTechs engaged in enhancing software quality, modernizing applications, and undertaking enterprise AI projects.
Source link: Beinsure.com.
