# Agentic AI
URL: https://docs.datarobot.com/en/docs/agentic-ai/index.html

> Create, connect, and test agentic workflows, integrate tools, and implement evaluation metrics.

# Agentic AI

Create, connect, and test agentic workflows, integrate tools, and implement evaluation metrics.

> [!TIP] New to the DataRobot CLI?
> Agentic workflows use the [DataRobot CLI](https://docs.datarobot.com/en/docs/agentic-ai/cli/index.html) ( `dr`) to set up templates, run local development, and deploy. If you haven't installed or used the CLI yet, see [Getting started with the DataRobot CLI](https://docs.datarobot.com/en/docs/agentic-ai/cli/getting-started.html).

- Build¶ Build and deploy agents from templates leveraging multi-agent frameworks.
- Evaluate¶ Chat with agents, compare responses, and implement evaluation metrics.
- Deploy¶ Register and deploy agentic artifacts and configure evaluation and moderation guardrails in Registry.
- Monitor & govern¶ Monitor deployment details, usage stats, metrics, logs, and moderation events for agentic artifact deployments in Console.
- DataRobot CLI¶ Use the DataRobot CLI to set up templates, run local development, and deploy.
- Agent Assist¶ An interactive AI assistant optimized for the development of AI agents.
- MCP¶ Integrate tools using MCP servers and connect IDEs and chat clients to your DataRobot MCP server.
- Vector databases¶ Create vector databases, LLM blueprints, and GenAI deployments.
- Prompt management¶ Create, manage, and share prompts that can be called into agentic workflows.
- RAG workflows¶ Create LLM blueprints, moderations, tests, and deployments.
- Code walkthroughs¶ Use code walkthroughs to implement GenAI.
- NVIDIA AI Enterprise integration¶ Use NVIDIA NIM and NeMo to accelerate GenAI application development.
- Feature considerations¶ Review LLM availability, GenAI capabilities, considerations, and troubleshooting tips.

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