Upcoming Webinar

How to Streamline AI Testing & Increase Transparency

April 29th | 3:30-4:00pm CET | Online

Join us for an introduction into cutting-edge methods to scalably and rigorously test AI systems. Learn to accelerate development, increase transparency, and build trustworthy AI, regardless of what type of AI models you’re developing (LLM, computer vision, classical ML, agentic AI etc.).

In this webinar, we’ll dive into:

  • how to ensure the quality and reliability of AI systems with automated testing for bias/fairness, robustness, performance and data distributions
  • how to bring transparency to AI systems and across the organization using analytics and summary dashboards  
  • concrete testing examples of LLM and computer vision models to demonstrate how evaluations can efficiently be done

Who Should Attend:

  • Data Scientists
  • AI Developers and Engineers
  • Machine Learning Engineers
  • Technical Stakeholders working with AI systems

Presenter:

Nikhil Menon
QuantPi
Solutions Engineer
Registration Form

About QuantPi

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QuantPi is pioneering the technologies of trust for the adoption of AI. Their end-to-end platform rigorously tests AI systems for unintended bias, robustness, compliance, and other critical metrics of performance. This offers AI lifecycle stakeholders a shared understanding of their AI systems—whether built in-house or third-party procured. At the heart of this platform is a powerful proprietary testing engine that uniformly assesses all types of AI (LLMs, computer vision, machine learning, agentic AI etc.). This delivers actionable insights and operationalizes internal AI policies and regulatory frameworks, such as the European AI Act.

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Funded by the European Union and emerging from one of the world’s leading information security research centers (CISPA), QuantPi is shaping a future where intelligent machines are deployed confidently and responsibly. Trusted by some of the world’s largest enterprises and institutions, QuantPi remains at the forefront of advancing trustworthy AI globally.

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