In this demo, we showcase how to leverage MLRun, Iguazio, and NVIDIA NIMs to deploy and monitor a generative AI model at scale, focusing on reducing risks and ensuring seamless performance. Using NVIDIA's NIMs, the demo demonstrates advanced methods in model monitoring, logging, and continuous fine-tuning.

In this webinar, we explored how to successfully deploy your Gen AI applications while mitigating these challenges, using NVIDIA NIM and MLRun.

See how to use MLRun 1.7 to fine-tune a generative AI banking chatbot, ensuring it answers only relevant banking inquiries. Watch the full tutorial and follow along!

This demo recorded during our MLOps Live Webinar #32 showcases a customer-facing AI agent developed for a jewelry retailer. This can be used as a marketing tool to offer personalized product recommendations and purchasing information and support.

In this MLOps Live session we were joined by Eli Stein, Partner and Modern Marketing Capabilities Leader at McKinsey, to delve into how data scientists can leverage generative AI to support the company’s marketing strategy. We showcased a live demo of a customer-facing AI agent developed for a jewelry retailer, which can be used as a marketing tool to offer personalized product recommendations and purchasing information and support. Following the demo, we held an interactive discussion and Q&A session. Enjoy!

In this session, we explored the unique challenges of implementing gen AI in production environments, when agents are in direct contact with your customers. We shared the Iguazio & MongoDB one-stop-shop solution for building gen AI applications that scale effectively and efficiently, with built-in guardrails and monitoring. We'll show how the end-to-end application lifecycle is addressed – From data management all the way to governance and monitoring in production.