Skip to main content
AI agents are available as an add-on for all plans. View pricing
AI agents automatically select the most relevant data models and metrics to answer your questions, build and execute queries with appropriate dimensions, metrics, and filters, and present results in the most insightful format.

​
What you’ll learn

This guide covers everything you need to know about AI agents in Lightdash:

Getting started

Using AI agents

Agent memory

Self-improvement

Best practices

Data access control

Evaluations

Verified answers

​
Key features

  • Natural language queries - Ask questions in plain English and get instant answers
  • Automatic visualizations - Get charts and tables generated based on your questions
  • Slack integration - Collaborate with your team directly in Slack channels
  • Memory and learning - Agents remember corrections and improve over time
  • Self-improvement - Agents can propose changes to your semantic layer (Beta)
  • Access control - Fine-grained control over data access and permissions
  • Multiple agents - Create specialized agents for different teams or use cases

​
Quick start

Ready to get started? Follow these steps:
1

Create your first agent

Set up a new AI agent in your Lightdash project, read the guide.
2

Configure access

Use tags to control which data the agent can access, read the guide.
3

Write instructions

Provide context to help the agent understand your business, read the guide.
4

Connect to Slack

Enable team collaboration through Slack, read the guide.