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Datazone Agents

Datazone Agents are custom AI assistants that can interact with your data through natural language conversations. Each agent is configured with specific data sources, tools, and models to help users explore, analyze, and extract insights from their data.

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What is an Agent?

An agent is an AI-powered assistant that:

• Understands natural language - Ask questions in any language
• Accesses your data - Queries datasets and views you’ve configured
• Uses tools - Executes SQL queries, runs Python code, creates charts, and more
• Provides insights - Analyzes data and delivers actionable answers

Unlike static dashboards, agents adapt to your questions in real-time and can handle complex, multi-step analysis automatically.

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Creating an Agent

1. Navigate to your Project page
2. Click the Add button (+ icon)
3. Select Agent from the dropdown

The agent creation flow will guide you through 4 steps:

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Step 1: Basic Information

Configure the basic settings:

• Name - A descriptive name for your agent (e.g., “Sales Analyzer”, “Customer Support Assistant”)
• Instructions - System prompt that defines the agent’s behavior, personality, and expertise
• Response Tone - How the agent communicates:
  • Casual - Informal, conversational style
  • Friendly - Warm and approachable
  • Technical - Precise and technical (default)
  • Educational - Explanatory and teaching-focused
  • Professional - Formal and business-like
• Response Length - How detailed responses should be:
  • Brief - Short, concise answers
  • Moderate - Balanced detail (default)
  • Detailed - Comprehensive, in-depth responses
• Language - The language your agent will use (supports multiple languages)

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Step 2: Model Configuration

Select your AI model provider and configure parameters:

• Model Account - Choose from configured Model Accounts (OpenAI, Anthropic, AWS Bedrock)
• Model - Select the specific model (e.g., GPT-4, Claude 3.5 Sonnet, GPT-4o-mini)
• Temperature - Controls creativity and randomness (0 = focused and consistent, 1 = creative and varied)
• Max Tokens - Maximum response length (higher = longer responses, higher cost)

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Step 3: Data Sources

Choose which datasets or views the agent can access. The agent will only be able to query data from these selected sources.

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Step 4: Tools

Enable optional tools that extend what your agent can do:

• Python Code Executor - Execute Python code for calculations and analysis
• Chart Generator - Create visualizations (line, bar, pie charts)
• Web Search - Search the internet for external information

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Using Your Agent

Once created, you can start chatting with your agent:

1. Click on your agent from the agents list in the project page.
2. Click to Go to Agent to open the chat interface.
3. Then click to New Chat to start a fresh conversation
4. Ask questions in natural language (in any language you configured)
5. The agent will automatically use its tools to analyze data and provide answers

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Agent Capabilities

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Natural Language Queries

Ask questions in any language:

• “What were our top 5 customers last month?”
• “Show me the revenue trend for Q4”
• “Which products have declining sales?”
• “Compare this quarter to last year”

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Multi-Step Analysis

Agents can perform complex analysis automatically:

1. Execute SQL queries to fetch data
2. Run Python code for calculations
3. Generate visualizations automatically
4. Provide insights and recommendations

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Context Awareness

Agents remember conversation history and can:

• Reference previous questions
• Build on earlier analysis
• Maintain context throughout the chat session

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Best Practices

1. Clear Instructions - Write specific system instructions that define the agent’s expertise and behavior
2. Right Data Sources - Only grant access to relevant datasets/views
3. Appropriate Model - Choose models that balance cost and capability for your use case
4. Use Views - Configure views for faster queries and better data access control
5. Test Thoroughly - Ask various questions to ensure the agent understands your data correctly

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Next Steps

• Chat with Your Agent
• Optimize Performance
• Configure Model Accounts