> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/ai-workbench/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/ai-workbench/_mcp/server.

> NVIDIA AI Workbench Example Projects

# NVIDIA AI Workbench Example Projects

Explore a diverse collection of NVIDIA-created example projects tailored to various AI tasks. These projects serve as practical references and starting points for your own development.

Each project is accompanied by detailed documentation and can be cloned and opened directly within AI Workbench using the Desktop App or CLI.

If you are already familiar with AI Workbench, and want to learn how to use an example project, see [Advanced Walkthrough: Hybrid RAG](/ai-workbench/quickstart/quickstart-hybrid-rag).
If you are just getting started with AI Workbench, see [Basic Quickstart](/ai-workbench/quickstart/quickstart-basic).

The following example projects are available:

- [Example Projects for Agentic AI](/ai-workbench/quickstart/example-agents) - Build, evaluate, customize, and secure AI agents through a hands-on workshop using NVIDIA NIM microservices, Nemotron models, and the NeMo platform.
- [Example Projects for Retrieval Augmented Generation (RAG)](/ai-workbench/quickstart/example-rag) - Implement advanced retrieval techniques to enhance generative models with multimodal document processing and enterprise-grade RAG pipelines.
- [Example Projects for Fine-Tuning Models](/ai-workbench/quickstart/example-fine-tuning) - Customize pre-trained models including Llama, Mistral, and SDXL to suit specific applications and datasets using parameter-efficient techniques.
- [Example Projects for Data Science Workflows](/ai-workbench/quickstart/example-data-science) - Utilize RAPIDS and other tools for efficient data processing, analysis, and machine learning workflows.
- [Example Projects for Blueprint Workflows](/ai-workbench/quickstart/example-blueprints) - Build enterprise-grade AI applications using NVIDIA Blueprints for PDF-to-podcast conversion, deep research assistants, and production-ready RAG solutions with NVIDIA NIM microservices.
- [Example Projects using NIM Deployments](/ai-workbench/quickstart/example-nim) - Build and deploy custom NVIDIA NIM microservices for scalable AI model serving and inference.

## Related Topics

**Learn the Concepts**

- [Add a Brev Instance](/ai-workbench/how-to/locations/add-brev)
- [How to Work with AI Workbench Projects](/ai-workbench/how-to/projects/overview)
- [AI Workbench Project Containers](/ai-workbench/concepts/single-container-concept)
- [Integrations and Credentials](/ai-workbench/reference/faq#integrations-and-credentials)
- [Applications](/ai-workbench/concepts/application-concept)
- [Version Control in AI Workbench](/ai-workbench/concepts/versioning-concept)