Quality Engineering for AI

Testing generative AI applications and chatbots requires creative thinking and is not the same as testing traditional software applications. Large Language Models and Retrieval Augmented Generation are undergoing rapid adoption across industries. Prolifics can help ensure they can be relied on.

GenAI applications are appearing in large numbers and have already proved their worth, while continuing to rapidly evolve. GenAI is being used in applications for text, images, video and audio, which all affect how testing of these application should be performed. Focusing on natural language, text-based applications, we find that corporate implementations of GenAI often include Retrieval Augmented Generation (RAG), which is a key consideration for testing. Testing GenAI solutions and LLM’s should include the usual types of tests carried out on software, but should also focus on bias, fairness, accuracy and completeness. Prolifics have a suite of offerings around testing GenAI Apps, which are detailed below.

  • Data Quality Testing

    We check that the data your applications rely on is accurate and free of errors before it can be trusted in a production environment.  Testing can be split into two parts, addressing any RAG system initially, before focusing on the LLM being used.

  • Bias and Fairness Testing

    Functional testing of the model and its prompts, including a focus on edge cases and boundary values, ensuring consistency and that small changes correctly update the output, with no bias or stereotyping.

  • Regression Testing

    Monitoring the behaviour of GenAI applications over time is a vital part of ensuring models do not drift and that answers are consistent with expected behaviour. Regression tests can be based on expected behaviour and scored responses, which are ideal for test automation.

  • Security Testing

    Ensures malicious prompts are unable to affect the application under test and that additional prompts are isolated accordingly, protecting GenAI applications.

  • Performance Testing 

    Where applications are planned to be used by large numbers of concurrent users and response times are important, performance tests should be carried out, to ensure applications can support the anticipated load – just as with traditional software applications.

  • Crowd Testing 

    Due to the nature of GenAI applications, testing by many users is likely to be an important part of a pyramid of tests needed to be confident in these apps, especially when considering exploratory testing and the ability to gain perspective of different social or ethnic groups.

Why Our Testing Approach Is Different?

Our approach to testing GenAI and LLMs is deeply integrated with the unique capabilities of our Innovation Centre, providing a substantial advantage to our clients. Here, we not only explore new AI technologies and architectures but also co-create with our clients to build disruptive AI solutions tailored to their industries.

Our approach is threefold:

  • Embrace: Through AI assessments, we help you adopt the right AI technologies that integrate seamlessly within your tech ecosystem.

  • Develop: We collaborate closely with your teams to enhance the delivery and quality of your applications.

  • Advance: We use advanced AI to increase the efficiency of your quality teams, ensuring they are more effective and innovative.

This holistic and forward-thinking strategy ensures that our testing services are not just comprehensive but also cutting-edge, enabling your business to leverage AI technologies confidently and effectively.

At Prolifics Testing, we work closely with you to understand what you need and create a testing plan that fits perfectly. This tailored approach helps you get the most out of GenAI, improving efficiency and innovation.

Contact us

Get in touch with our AI experts to ensure your GenAI apps are ready for launch!

Scroll to top