RAG Pipelines Letting You Down?
How The Fitch Group Handles High-Similarity, Frequently Updated Document Sets in Financial Services
Struggling with RAG pipelines in high-stakes environments? In this insightful talk, Pablo Vega-Behar, Head of AI Implementation at Fitch Group, unveils advanced strategies for handling high-similarity, frequently updated document sets in financial services. Learn how Fitch Group’s Emerging Tech team optimizes retrieval accuracy and generation relevance using innovative chunking, embedding, indexing techniques, hybrid retrieval methods, and more. This session also covers actionable insights for improving application performance and designing robust development environments for seamless collaboration between data scientists and ML engineers.
Ideal for advanced data scientists and engineers, this talk dives into real-world use cases, proven solutions, and practical tips to refine your RAG systems. Don’t miss this opportunity to elevate your understanding of NLP, AI, and machine learning applications in financial services!
Pablo Vega-Behar
Head of AI Implementation at The Fitch Group
Pablo Vega-Behar is the Head of AI Implementation at Fitch Group, a financial services firm. With over a decade of experience in data science and AI, his expertise spans multiple industries including healthcare, consulting, civil engineering, and finance. He earned his Ph.D. in Engineering from Georgia Tech and is currently focused on applied generative AI, automating content generation in regulated industries, as well as machine learning applications for financial analysis and risk management
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