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This 41-minute webinar explores how organizations can prepare AI-ready data to maintain competitive advantage in an era where large language models are becoming commoditized. Discover why companies must focus on first-party data strategies rather than simply integrating OpenAI APIs as LLMs increasingly train on shared public datasets. Learn about the current state of enterprise AI reliability, the evolving AI stack, and essential data architectures for building dependable generative AI applications including RAG and fine-tuning approaches. The presentation covers key factors that make data AI-ready, common reasons AI applications fail, and best practices for detecting and resolving data incidents. Watch a detailed demonstration of the Monte Carlo platform, understand its operational aspects, cost scaling with data growth, and pricing model. Perfect for data scientists, engineers, and business leaders navigating the challenges of implementing reliable and scalable AI systems in their organizations.
