George Miranda, VP of Marketing, InsightFinder AI Abstract As AI models move from pilot to production environments, ensuring AI model reliability and performance becomes increasingly difficult. Many solutions have evolved into “Composite AI” systems—combining various traditional machine learning (ML) models and large language models (LLMs) both open-source and commercial sources for more robust capabilities. These systems not only involve the models themselves but also rely on complex data pipelines and robust IT infrastructure to remain operational and effective. Additionally, AI & ML teams are closer than ever to the customer experience. Operating in production brings a new set of challenges and expectations. Many teams are still in development, but those already on the front lines have learned (often, the hard way) that many traditional tools and techniques fall woefully short. In this talk, I will explore the key challenges in delivering reliable and responsible enterprise AI and introduce a new approach to intelligent and efficient monitoring, evaluation, and governance that is designed to meet these challenges in production.
Interviews
Ai4 Presentation – Building Reliable AI Apps in Production – Observability for an AI World With InsightFinder AI
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