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Explore insights on QA of LLM applications, testing automations, and ensuring fairness in AI models. Stay informed with our expert articles on identifying and mitigating bias, enhancing reliability, and safeguarding against adversarial behaviors in your deployments.
Knowledge
8 mins read

Executing Context-Aware Generative AI Testing: A Unified Team Effort

The rise of generative AI (Gen AI) applications is poised to revolutionize the way businesses operate, offering unprecedented capabilities in areas like customer service, content creation, and data analysis. However, the complexity and unpredictability of non-deterministic applications present unique challenges when it comes to testing and evaluation.
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Knowledge
Knowledge
8 mins read

Executing Context-Aware Generative AI Testing: A Unified Team Effort

The rise of generative AI (Gen AI) applications is poised to revolutionize the way businesses operate, offering unprecedented capabilities in areas like customer service, content creation, and data analysis. However, the complexity and unpredictability of non-deterministic applications present unique challenges when it comes to testing and evaluation.
Read post
Knowledge
8 mins read

1000+ Global AI Regulations - Turning AI Regulations into Opportunities: Are You Ready?

In this post, we discuss the rapidly evolving landscape of AI governance and regulation, particularly focusing on Generative AI. We highlight the challenges businesses face in keeping up with global AI policies, with over 1000 AI initiatives from 69 countries, territories, and the EU.
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Case Study
7 min read

Gen AI Chatbots in the Insurance Industry: Are they Trustworthy?

As generative AI chatbots continue to make their way into regulated industries like insurance, assessing their trustworthiness becomes essential. In this post, we present findings from testing two generative AI chatbots employed by leading insurance companies in the DACH region (Germany, Austria, Switzerland), covering more than 70 million clients.
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Knowledge
8 min read

Ensuring Trustworthy AI: Why Quality Assurance Matters

In this blog post, we’ll explore the importance of QA in identifying issues like fairness, robustness, and transparency, and how tailored testing solutions can mitigate risks associated with AI, ensuring your applications deliver consistent, high-quality outcomes in real-world environments.
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Knowledge
6 min read

LLM Application Testing: 3 Key Dimensions for Trustworthy AI - Robustness, Reliability, and Compliance

Learn how to ensure robustness, reliability, and compliance in LLM application testing with these essential strategies and best practices.
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Knowledge
10 min read

Losing my Religion: Testing for Bias in LLM Applications

In this post, we delve deeper into one crucial aspect of compliance: ethical considerations, specifically focusing on bias and toxicity in LLM applications.
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