TIGEREYE Inc. and GENZ Inc. Announce New Testing Service to Support AI System Quality Improvement—Specialized Testing Service for AI Products to Ensure Quality and Reliability
On February 14, 2025, TIGEREYE Inc. (hereinafter "TIGEREYE") and GENZ Inc. (hereinafter "GENZ") announced a new testing service designed to support the quality improvement of AI systems. This service integrates TIGEREYE's advanced algorithmic technology with GENZ's extensive industry experience to identify and analyze AI-specific risks while maximizing system safety and performance. As AI technology evolves, the service will provide a comprehensive testing solution leveraging both companies' expertise to support the construction of more accurate and reliable AI systems.
Service Introduction
Elevating AI Solutions to the Next Level with TIGEREYE's Technology and GENZ's Experience
AI systems, reliant on complex algorithms and vast data, face various risks that can impact accuracy and reliability. Data bias, incorrect learning patterns, and security vulnerabilities are among these risks, potentially leading to performance degradation and severe errors. The advanced algorithmic prowess of TIGEREYE and the rich experience and industry knowledge of GENZ come together to provide an optimal and effective testing strategy specialized for AI systems.
Total Support for AI Safety and Quality
Developing AI systems involves inherent risks and challenges. TIGEREYE and GENZ offer comprehensive support through AI-specific consulting and testing to ensure system quality and safety.
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Total Support for AI Safety and Quality
Developing AI systems involves inherent risks and challenges. TIGEREYE and GENZ offer comprehensive support through AI-specific consulting and testing to ensure system quality and safety.
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AI Specialized Testing Service
The testing strategy for AI models is tailored to the characteristics of the project requirements, verifying the overall system performance and safety. Flexible application of testing methods suitable for AI systems, such as regression tests, classification tests, and black-box tests, enhances reliability.
Three Reasons to Choose GENZ
1. Comprehensive AI Quality Assurance Framework Covering All Phases
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AI systems face various risks at each phase of development—from requirement definition to design and implementation, including data bias, incorrect learning patterns, and security vulnerabilities. GENZ provides a unique AI quality assurance framework that covers all phases, designing and executing suitable testing strategies to consistently improve system quality. This approach effectively manages the complex risks of AI systems, ensuring reliable operation.
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2. Flexible and Rapid Response by AI Expert Team
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GENZ's AI expert team leverages extensive experience in system testing and vulnerability diagnosis to consistently support machine learning model testing. They propose optimal testing methods and vulnerability diagnoses tailored to customer business requirements, minimizing risks throughout the development process. Their flexible and rapid response effectively utilizes resources, optimizing the balance between quality, cost, and delivery time.
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3. Proven Track Record and High Customer Satisfaction
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GENZ boasts a rich history across a broad range of industries, from startups to enterprise companies. They have provided quality assurance for systems, including AI, in various fields such as healthcare, web applications, and payment services. Particularly, they conduct multifaceted evaluations of system safety and performance, building long-term partnerships with many clients. GENZ continually strives to master new technologies, providing solutions that accommodate the latest technologies.
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Impact of Service Implementation
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Enhancing System Reliability and Stability
By implementing AI testing services, overall system reliability and stability are improved. Rigorous testing verifies the accuracy and consistency of AI models, preventing operational issues. This enables long-term stable operation of systems.
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Improving Customer Satisfaction and Brand Trust
Providing high-quality AI systems improves user experience, increasing customer satisfaction and enhancing brand trust. This strengthens the competitive edge of the business.
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Reducing Business Risks
The service minimizes business risks associated with system malfunctions and performance deficiencies. By identifying potential problems early and implementing efficient testing strategies, high-quality systems are achieved while controlling costs.
AI System Testing Process Flow
Requirement Definition and Hearing
The first step involves confirming the requirements for the AI system with the customer, discussing the project's scale, objectives, and schedule. Details on the expected outcomes and use scenarios of the AI system are also thoroughly reviewed.
Risk Analysis and Test Planning
Based on the hearing, overall system risks are analyzed, and risk mitigation strategies tailored to the AI model's characteristics are considered. Subsequently, a concrete test plan is formulated, determining the testing perspectives and items.
Test Design and Environment Preparation
Test designs are created based on the test plan, organizing the necessary testing items. The environment and equipment needed for testing are also prepared. If special equipment is required, arrangements are made with the customer to ensure full preparedness.
Test Execution and Defect Reporting
Tests are conducted according to the established items, and any detected defects are promptly reported with evidence, supporting the development team's efficient response.
Defect Correction and Retesting
After the reported defects are corrected, retesting is conducted to ensure the corrections are accurately reflected, further enhancing system quality.
Result Reporting and Delivery
Upon completion of the tests, a detailed report is prepared and delivered, including the testing content, defect details, and improvement suggestions, designed to help customers easily understand the system's status.
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