From Pilot to Production: Explainability, Auditability and What Actually Matters

67% of AI projects fail to make it to production.

The usual suspects are well known - stakeholder issues, data problems, unclear goals. But there is another layer that gets less attention: models that work in the lab but cannot survive the transition to a real operating environment, where results need to be explained, decisions need to be audited, and trust needs to be earned from people who were not in the room when the model was built.

In this webinar, Dr. Christian Debes, Co-Founder of Spryfox, and Dr. Ágoston Török, Head of AI Technology at Straumann Group, bring their combined experience from decades of getting AI models from experiment to production - including in some of the most demanding regulated environments where explainability and auditability are not optional.

Join us to learn:

• What explainability and auditability actually require in practice
• Why most first results are wrong and what it takes to get to ones you can trust, and
• What the transition from pilot to production demands from teams and processes that most pilots never anticipate.

This session is ideal for AI and Data Science leaders, AI/ML Product Managers, Risk or Compliance professionals and Machine Learning Engineers responsible for bringing AI systems into real-world, production environments.