Testing AI systems

How we support you

Our services are modular and can be optimally tailored and combined to meet your needs:

AI testing strategy

We analyze the use of your AI systems and update your existing testing strategy, or develop complete testing strategies from scratch. The focus is on the safe and functionally correct use of the desired AI technology. Sustainable and able to keep pace with the rapid pace of development in this field.

• Assessment of current AI usage, identification of risks and testing gaps (e.g., "What happens when the model receives different data?")
• Development of an individual testing strategy for your AI applications (e.g. Generative AI, Machine Learning, Chatbots)

Architecture and data review

AI systems are often highly data-driven. We consider processed data holistically and comprehensively. An important aspect is the assessment of data security.

• Analysis of the models used, data pipelines, training and deployment environment
• Examination for data quality, bias, non-determinism and concept drift
  

Test methodology for AI systems

Tailor-made testing procedures ensure risk-based and cost-optimized testing.

• Special test types for AI: semantic validation, oracle approaches, metamorphic testing, robustness and adversarial testing
• Integration of AI testing methods into CI/CD, automation and quality assurance
  

Test data

Regardless of whether AI systems need to be validated for accuracy or trained, secure and relevant data is an essential success factor. We are familiar with both the market-leading solutions and the specialists in the field of test data for AI systems.

• Definition and specification of required safe test data, taking into account regulatory and legal requirements
• Selection and implementation of suitable solutions

Tool and technology consulting

Efficient testing of AI systems is impossible without test automation and structured test management. We help you find the setup that best suits your requirements.

• Selection of suitable testing tools and frameworks for AI quality assurance (e.g., visual testing, self-healing, generative test case creation)
• Implementation, integration, deployment and maintenance of state-of-the-art testing technologies
  

Governance, compliance & risk management

In addition to the classic risks of software errors, the dangers of creeping malfunctions, as well as regulatory and legal requirements, must be consistently excluded in AI systems.

• Advice on regulatory requirements (e.g. EU AI Act, data protection, fairness, transparency)
• Implementation of processes for documented test execution and traceability

Implementation & Monitoring

We support you throughout the entire implementation process. Whether leading the project, acting as an extended workbench, or providing targeted consulting. Rapid technological advancements demand a strategy that can adapt to changes. We help you profitably implement any trend.

• Conducting pilot and production tests of AI systems
• Monitoring of model behavior, drift, performance and quality throughout the life cycle

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Why our customers choose Infometis for AI testing

Infometis has been committed to the targeted use of modern technologies for IT services for decades. Since the advent of AI systems, we have invested in training, practical experience, and technology partnerships, and are actively involved in the community. As a result, Infometis maintains the usual technological advancements in AI, enabling us to align innovations with customer needs. Furthermore, we are actively involved in shaping curricula for quality assurance in artificial intelligence at international educational institutions.

• Infomets are constantly expanding their knowledge in AI topics
• We design our own training courses and our practitioners teach them
• We know the market and the technology partners thanks to our collaborations
• We have proven implementation experience in AI projects and have developed our own products