95% of RAG hallucinations are generated by the RAG, not the LLM. But why? In this talk, we'll discuss the hard data engineering problems of building highly accurate RAG systems and how to fix them. You'll see how companies like Air France are getting 95% accuracy or better.

Recorded live in San Francisco at the AI Engineer World's Fair. See the full schedule of talks at https://www.ai.engineer/worldsfair/2024/schedule & join us at the AI Engineer World's Fair in 2025! Get your tickets today at https://ai.engineer/2025

About Benjamin
Over a two decade career, Ben has designed CMOS chips for quantum computing, developed VPN architectures for mobile and pioneered consumer AI at IBM Watson and Weather Channel. He has 21 patents and a PhD in physics. In 2019, he launched EyeLevel.ai to help connect the world’s private data to LLMs.

AI Engineer

Ben, co-founder of EyeLevel, discusses the company’s advanced RAG (Retrieval-Augmented Generation) platform that optimizes document retrieval accuracy using no-code tools and APIs. EyeLevel's unique approach involves addressing common content ingestion issues and employing semantic objects to enhance search accuracy, achieving 98% accuracy in complex real-world documents and outperforming other market solutions.

EyeLevel Launch: Your RAG is Tripping, Here's the Real Reason Why