omniture

GienTech transforms enterprise software testing with the launch of a powerful AI-driven end-to-end solution

GienTech
2024-12-19 11:35 672

Next-generation Testing Center of Excellence (TCoE 3.0) integrates AI, ML, and automation to make enterprise software testing faster, more responsive and efficient

HONG KONG, Dec. 19, 2024 /PRNewswire/ -- Digital transformation specialist GienTech is revolutionizing the way enterprises approach software testing with the launch of a powerful new Testing Center of Excellence (TCoE 3.0) solution. Built on a platform of artificial intelligence (AI) and incorporating machine learning (ML), automation, and agile testing methodologies, TCoE 3.0 will support organizations to rapidly and efficiently develop mission-critical software for reliable and stable real-world use.

Enterprise software testing is extremely complex and time-consuming. According to Gartner*, product-testing teams will continue to face increasing complexity in applications and architecture, as well as shorter development cycles, in coming years. This pressure will be made more acute by the ongoing shortage of skilled engineers and the need to meet compliance regulations for data privacy and accessibility. At the same time, teams need to continue to automate an ever-growing backlog of manual tests. GienTech is empowering organizations to overcome these obstacles with an end-to-end solution that uses Generative AI to substantially streamline and enhance enterprise software testing.

William Wong, Senior Vice President of GienTech, said: "We are on a mission to make software testing more intelligent, agile, and efficient, while also reducing costs and labour intensity. TCoE 3.0 is a comprehensive end-to-end solution designed to standardize, centralize, and optimize enterprise software testing using AI, ML, and automation. It augments your software quality assurance team and is ideal for demanding environments, like the banking and finance sector, where complex system architectures, custom-built legacy systems, and highly sensitive data are the norm."

Key features of TCoE 3.0 include:

  • AI-powered test case generation: TCoE 3.0 leverages large language models (LLMs) to analyse business requirements and automatically generate test cases. This approach ensures that the test cases are aligned with business objectives throughout the end-to-end testing. By automating test case preparation and enhancing agility, TCoE 3.0 enables testing teams to achieve broader coverage with minimal additional effort.

  • AI-powered script creation and auto-execution: TCoE 3.0 converts natural language descriptions of test scenarios into executable test scripts and automates the execution of these scripts for end-to-end coverage. This innovation simplifies testing for dynamic user interfaces and custom workflows, empowering non-technical users to create test scripts. It effectively covers a wide range of scenarios across complex architectures, reduces manual tasks, and significantly streamlines testing efforts. 

  • Smart and scalable adaptive testing: TCoE 3.0 incorporates self-adapting capabilities to manage changes in application flows as well as self-healing capabilities to automatically adjust to user interface changes. By seamlessly adapting to continuous software updates, TCoE 3.0 minimizes the need for frequent script maintenance due to minor changes, significantly reducing the time, effort, and costs involved in test script upkeep.

The launch of TCoE 3.0 caps off a year of great strides in AI by GienTech. In 2024, GienTech launched the "ORIGIEN AI+" initiative to spearhead breakthroughs in AI-related product innovation, dataset construction, and model training. It has already introduced intelligent solutions to enterprises across various industries, including finance, energy, and manufacturing. In April, GienTech signed a strategic cooperation agreement with Hong Kong Applied Science and Technology Research Institute (ASTRI). The first fruit of this collaboration is the newly released Financial Intelligent Assistant, a comprehensive toolkit built on GienTech's AI agent technology framework and ASTRI's RAG framework to help financial sector enterprises accelerate AI application development and digital employee adoption. Earlier this month, GienTech unveiled the ORIGIEN Financial Large Language Model, which is tailored exclusively for the financial sector. The model enhances financial insights and applications through targeted training and tuning with 700GB of financial data, focusing on banking scenarios to ensure precise alignment with industry needs.

"With the explosive growth of technology, the application of AI is becoming increasingly practical, particularly in the highly digitized financial sector, where AI is experiencing large-scale adoption. The industry requires not merely AI products or models, but a true realization of enterprise intelligence that transforms business models through AI. Centred around the application and scenarios, we are committed to unlocking the value of AI application. Combining advances in AI technology with our strengths in infrastructure, consulting, software, data governance, and large-scale customized services, GienTech can help enterprises achieve intelligent digitalization, enhance productivity, and improve profitability," Wong continued.

* Gartner, "Market Guide for AI-Augmented Software Testing Tools" (13 February, 2024)

About GienTech

Founded in 1995, GienTech is an expert in intelligent digitalization strategies and software solutions, specializing in the financial and other key industries. GienTech has more than 40,000 employees across China and in overseas markets, serving over 800 financial institutions and more than 160 Fortune 500 companies. GienTech has ranked first in the IDC China banking IT solution market for seven consecutive years and has been selected in the global top 100 in the IDC Financial Insights FinTech ranking for nine consecutive years. Its strict quality and management principles have passed CMMIL5, ISO27001, ISO9001, ISO20000 and many other international certifications.

Source: GienTech
collection