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.

📂 GitHub: https://github.com/mlrun/demo-nim-application

🎥 Webinar Link: https://www.iguazio.com/sessions/deploying-gen-ai-in-production-with-nvidia-nim-mlrun/

🔗 Useful Links:
🌐 Website: www.iguazio.com
💻 MLRun Website: https://www.mlrun.org/
📚 AI Blogs: https://www.mlrun.org/blog/
📂 GitHub: https://github.com/mlrun/mlrun

💡 Stay Connected:

Slack Channel : https://go.iguazio.com/mlopslive/joincommunity
Book a Demo: https://go.iguazio.com/book-a-live-demo-today

About Iguazio

Iguazio, part of McKinsey's QuantumBlack, provides an AI platform for developing, deploying, and managing ML and GenAI applications in live business environments. Its automation and orchestration capabilities enable enterprises to scale AI models in real time, deploy them across multi-cloud, on-prem, or edge environments, and mitigate GenAI risks. Iguazio powers use cases like agent copilots, chatbot automation, fraud detection, real-time recommendations, and predictive maintenance, helping organizations efficiently scale AI strategies. Acquired by McKinsey in 2023, Iguazio transforms AI visions into reality.

About MLRun

MLRun is an open MLOps framework for building and managing continuous ML and GenAI applications. It integrates with development and CI/CD environments, automating data delivery, ML pipelines, and applications to reduce engineering effort, production time, and resources. MLRun fosters collaboration across data, ML, software, and DevOps teams, enabling faster, continuous improvements.

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