The flagship initiative within the Disrupt (AI) Summit series, designed to explore the transformative impact of Generative AI across the technology and product landscape. Over two days, Gen AI Unfold will bring together senior AI & technology leaders, product managers, and engineers to address the challenges and opportunities shaping the future of business and innovation.

Followed by a series of activations and community events, Gen AI Unfold will host two focused event tracks— PLG Disrupt AI Summit Athens (dedicated to product development and management), and Disrupt AI Summit Athens (tailored for software engineers and tech professionals) – which will offer a comprehensive exploration of AI’s evolving role in tech and product teams.

Attendees will gain insights into the latest advancements in Generative AI, practical applications across industries, and the strategic leadership required to harness these technologies for organizational growth.

Featuring in-person technical workshops, hands-on sessions, real-world case studies, and dynamic discussions with global experts, Gen AI Unfold is the ultimate hub for exploring the latest breakthroughs in AI and the rise of agentic technologies—where innovation, autonomy, and leadership converge.

Feature Session: RAG in Production: Challenges, Techniques and Solutions

You may have seen headlines about AI systems recommending that users eat rocks or put glue on pizza—classic examples of hallucinations. Retrieval-Augmented Generation (RAG) is an architectural approach designed to reduce these failures by grounding model outputs in reliable, external knowledge.

At its core, RAG combines two components: a retriever (typically a vector database) that fetches relevant context, and a generator (an LLM) that uses this context to produce the final response. While the concept is deceptively simple, building and deploying RAG systems in production introduces a range of real-world challenges—from data quality and retrieval accuracy to latency, evaluation, and operational complexity.

In this talk, you’ll explore the most common failure modes of production RAG systems and learn practical techniques to mitigate—or eliminate—them, enabling more reliable, trustworthy AI applications.

Location

Athens, Greece