Starburst AI Agent#

The Starburst AI Agent is a chatbot that helps you analyze data by converting natural language questions into SQL queries and analyzing their results. Starburst Agent can generate and execute SQL queries and provide metadata about available datasets.

Requirements#

To use AI Agent, you need:

  • A valid AI_WORKFLOWS license.

  • Access to at least one configured language AI model.

Considerations#

  • AI Agent sessions can be stored in coordinator memory or the Insights database. Each session supports one SQL query. The Agent can answer as many questions about the data produced by the query. The Agent can respond to both data-related and metadata-related questions. For example, you can ask questions such as Which columns are related to customer behavior?.

  • AI Agent is conversational. You can reference earlier questions and answers in the same session. For example, after asking which columns are related to customer behavior, you may follow up with, Show trends in customer spend over the last two years, grouping by the customer behavior dimensions identified in your previous answer.

  • Data product enrichment affects AI Agent’s response quality. For example, the more detailed a data product’s metadata is, the higher quality the agent’s response may be.

  • AI Agent can now use tools and run multiple queries as need to analyze data. The agent executes these steps automatically and does not request prior approval. You cannot edit a query produced by AI Agent.

Configuration#

To configure AI Agent, add the following property to your coordinator configuration file:

starburst.agent.enabled=true

Session storage#

Configure how AI Agent’s sessions are stored. You can store sessions in coordinator memory, where they are not persisted, or in the insights database, where they are persisted.

ai.agent.session-storage=INSIGHTS

The possible values are: IN_MEMORY and INSIGHTS. By default, AI Agent session storage is set to INSIGHTS.

Using AI Agent#

To open the chat dialog and begin a session with AI Agent:

  1. Navigate to the Data products tab in the Starburst Enterprise web UI.

  2. Select an existing data product.

  3. Click AI Agent Icon Sparkle AI Agent’s icon at the bottom-right of the screen.

  4. In the chat interface:

    • Use the left drop-down menu to select a persona.

    • Use the right drop-down menu to select an AI model. If only one model is configured, it is preselected.

  5. Enter a question or prompt in the text area.

  6. Press Enter or click the send submit button.

Session history#

Use session history to review past AI Agent responses, including how different personas and AI models affected the answers. Session history shows the steps the AI Agent performed, including any tool calls and SQL queries executed during the conversation.

chat Chats are located on the left of the AI Agent chat dialog. If chats are stored in coordinator memory, previous chats are not displayed.

Manage chats#

Each conversation appears in the chat Chats list.

  • To rename a chat, hover over it and click the more_vertoptions menu, then select Rename.

  • To delete a chat, hover over it and click more_vertoptions menu, then select delete.

  • Use the search search bar to find previous chats by name.

The following describes the icons used in the AI Agent chat dialog:

AI Agent chat dialog icons#

Icon

Description
content_copy

Copy the agent’s response to clipboard.

download_2

Download the agent’s response.

send

Submit a question.

close

Minimize the AI Agent chat dialog.

more_vert

Open the options menu.

add

Start a new chat.

search

Search bar.

edit

Rename a chat.

delete

Delete a chat.

Personas#

AI Agent supports three personas. Each persona tailors its responses to suit different user roles and goals. The following sections describe the Executive, Analyst, and Data engineer personas.

Executive#

Provides high-level summaries tailored to executives and decision-makers.

  • Focuses on business insights and trends

  • Omits technical detail unless explicitly requested

  • Presents concise bullet points for quick understanding

Analyst#

Offers detailed analytical summaries suitable for analysts and data scientists.

  • Includes statistical analysis and relationships in the data

  • Adds contextual information and potential implications

  • May include suggestions for further exploration

Data engineer#

Provides technical summaries tailored to engineers.

  • Focuses on structure, data quality, and metadata

  • Includes schema details, cardinality, and patterns

  • Highlights potential data issues or anomalies