Example Projects for Agentic AI#

These example projects demonstrate how to build, evaluate, and deploy AI agents using NVIDIA AI Workbench. The projects showcase:

  • Agent architectures that connect large language models to tools and external data.

  • Agentic Retrieval Augmented Generation (RAG) for autonomous information retrieval.

  • Evaluation techniques for measuring agent quality, including LLM-as-judge approaches.

  • Model customization with parameter-efficient fine-tuning and reinforcement learning.

  • Safety and security hardening for agents before production deployment.

These examples are ideal for developers and organizations looking to:

  • Learn agent development through hands-on, notebook-based modules.

  • Build agents with NVIDIA NIM microservices, Nemotron models, and the NeMo platform.

  • Evaluate, customize, and secure agentic systems for production use.

Example Project on GitHub

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Build An Agent Workshop

A six-module, hands-on workshop for building, evaluating, customizing, and securing AI agents with NVIDIA NIM and NeMo.

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The Build An Agent Workshop is also available as an NVIDIA Brev Launchable for one-click deployment on a cloud GPU.