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LLM Monitoring

In this demo, you'll learn how to add guardrails and evaluate a banking chatbot using model monitoring and continuous fine-tuning techniques in MLRun. The video demonstrates how to enhance chatbot robustness, reduce risks, and automate improvements through data logging, LLM monitoring, and fine-tuning pipelines, and finishing with the deployment of a refined model. 📂 GitHub Demo: https://github.com/mlrun/demo-llm-mon... 🎥 Watch the full webinar: https://www.iguazio.com/sessions/impl... 🖥️ Related blog: https://www.iguazio.com/blog/how-to-i... 🔗 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/join... Book a Demo: https://go.iguazio.com/book-a-live-de... 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.