Suman Debnath, Principal Developer Advocate At AWS On Architecting Modern AI With Retrieval-Augmented Generation (RAG)

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Overview

Retrieval-Augmented Generation (RAG) is not just a buzzword — it’s rapidly becoming the core strategy behind scalable, enterprise-grade GenAI systems. In this exclusive episode of Discover Dialogues, we speak with Suman Debnath, Principal Developer Advocate for Machine Learning at Amazon Web Services (AWS), about the future of intelligent agents, the evolving role of retrieval, and why multimodal capabilities are transforming how businesses deploy AI.

With over 100 speaking engagements across PyCon, PyData, ODSC, and AWS re:Invent, Suman brings a rare combination of deep technical expertise and the ability to break down complex concepts in a way that resonates with business decision-makers and developers alike.

The Big Idea: AI That Retrieves Before It Generates

At the heart of the conversation is a simple but powerful insight — hallucination in AI isn’t a model problem, it’s a retrieval problem. Suman uses a vivid analogy: “If your librarian gives you the wrong book, no matter how hard you read it, you’ll never find the answer.” That’s what happens when your GenAI system pulls incorrect or insufficient data into its generation pipeline.

Enter RAG, a method that improves model accuracy by grounding it in real, relevant external data — whether that’s PDFs, internal documentation, product databases, or sensor feeds.

Beyond Text: Building Multimodal AI Agents

Suman also walks us through the next frontier — Agentic RAG with Vision-Language Models. As enterprises look to combine structured and unstructured data — like documents, visuals, and even voice — traditional retrieval falls short. Here, Suman introduces Colpali, an approach designed to optimize multimodal search and decision-making.

If your AI needs to look at a form, read text, understand a chart, and make a decision — you’re already in the realm of multimodal AI. And according to Suman, this is exactly where industries like healthcare, logistics, and finance are headed.

Why This Episode Matters

This conversation goes beyond theory. It’s a playbook for:

Product and engineering teams looking to implement GenAI
CXOs trying to future-proof AI investments
Technical leaders seeking clarity on AI infrastructure options

Suman’s combination of humility, clarity, and deep expertise makes this a must-listen episode — especially for those navigating the noisy, fast-moving world of generative AI.

About Suman Debnath

Suman Debnath is a seasoned technologist and Principal Developer Advocate at AWS. He has delivered over 100 keynotes and workshops worldwide and now leads machine learning advocacy through tools like Bedrock, SageMaker, and vector search. His work focuses on making AI practical and scalable for real-world enterprise challenges.

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RAG GenAI Multimodal AI Agentic Systems Amazon Bedrock Vision-Language Models AI Retrieval AWS AI Discover Dialogues

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