Free Lesson

Open-source AI in Production w/ Nvidia

Part of The AI Builders Summit

Hosted by Kiriti & Aish and Chris Alexiuk

Fri, Aug 21, 2026

4:00 PM UTC (1 hour)

Virtual (Zoom)

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Featured in Lenny’s List
Building Agentic AI Applications with a Problem-First Approach
Aishwarya Naresh Reganti and Kiriti Badam
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What you'll learn

Move beyond the local prototype

What actually breaks when a laptop demo meets real production load

Choose the right infrastructure

How to pick the GPUs and infrastructure your workload needs instead of over- or under-provisioning.

Build with open models like Nemotron

Where open models fit, and how to put NVIDIA's Nemotron family to work inside real systems.

Support serious workloads in production

What it takes to run AI systems that stay fast and reliable under real user demand.

Why this topic matters

Most AI projects run beautifully on a laptop and buckle the moment they meet real workloads. This session is about what changes when you move from a local prototype to infrastructure that can actually carry serious load: choosing the right GPUs and models, working with open models like NVIDIA's Nemotron, and standing up systems that stay reliable in production.

You'll learn from

Kiriti & Aish

AI practitioners with combined 20+ years of experience

Aishwarya Naresh Reganti is the founder and CEO of LevelUp Labs, a human-first AI startup that helps develop and deploy production-ready generative AI solutions for mid to large enterprise clients. With over 9 years of experience in machine learning, she has published more than 35 research papers at top-tier AI conferences, including NeurIPS, AAAI, and CVPR.

Kiriti Badam is a member of the technical staff at OpenAI Codex, with over a decade of experience designing high-impact enterprise AI systems. He specializes in AI-centric infrastructure, with deep expertise in large-scale compute, data engineering, and storage systems.

Chris Alexiuk

Senior Product Research Engineer Nvidia

Chris Alexiuk is a Senior Product Research Engineer at NVIDIA, where he builds the technical assets that help developers get the most out of NVIDIA's AI tools. He comes from a machine learning and data science background, co-founded AI Makerspace, and is deeply immersed in everything to do with large language models.

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