We use essential cookies to make our site work. With your consent, we may also use non-essential cookies to improve user experience, personalize content, customize advertisements, and analyze website traffic. For these reasons, we may share your site usage data with our social media, advertising, and analytics partners. By clicking ”Accept,” you agree to our website's cookie use as described in our Cookie Policy. You can change your cookie settings at any time by clicking “Preferences.”

Artificial Intelligence

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

By Nikhil Sonawane

Overall Rating

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.

Fri, Jun 27, 2025

Liked what you read? That’s only the tip of the tech iceberg!

Explore our vast collection of tech articles including introductory guides, product reviews, trends and more, stay up to date with the latest news, relish thought-provoking interviews and the hottest AI blogs, and tickle your funny bone with hilarious tech memes!

Plus, get access to branded insights from industry-leading global brands through informative white papers, engaging case studies, in-depth reports, enlightening videos and exciting events and webinars.

Dive into TechDogs' treasure trove today and Know Your World of technology like never before!

Disclaimer - Reference to any specific product, software or entity does not constitute an endorsement or recommendation by TechDogs nor should any data or content published be relied upon. The views expressed by TechDogs' members and guests are their own and their appearance on our site does not imply an endorsement of them or any entity they represent. Views and opinions expressed by TechDogs' Authors are those of the Authors and do not necessarily reflect the view of TechDogs or any of its officials. While we aim to provide valuable and helpful information, some content on TechDogs' site may not have been thoroughly reviewed for every detail or aspect. We encourage users to verify any information independently where necessary.

Join The Discussion

Join Our Newsletter

Get weekly news, engaging articles, and career tips-all free!

By subscribing to our newsletter, you're cool with our terms and conditions and agree to our Privacy Policy.

  • Dark
  • Light