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Available for Plus plan and above
Teable’s AI Chat is a context-aware intelligent assistant that understands your data structure. Unlike generic AI, it knows your current table, view, and fields, allowing for precise data manipulation and analysis.

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Getting Started

You can start a conversation from anywhere in your Space by clicking the “Sparkles” icon in the top right corner.

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Suggested Prompts

When you open AI Chat, you’ll see rotating prompt suggestions to inspire your first query:
  • “Analyze the sales trend for this month”
  • “Create a bar chart of revenue by category”
  • “Build an inventory management app from this table”
Click any suggestion or type your own question to get started.

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Context Scope

AI Chat is context-aware. It automatically identifies:
  • Current Table: Queries are scoped to the active table by default.
  • Current View: If you have filters applied, AI respects them.

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Core Capabilities

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1. Deep Data Analysis (Text-to-SQL)

Teable’s AI Chat doesn’t just guess; it essentially functions as a professional Data Analyst.
  • SQL Generation: It converts your natural language questions into complex, executable SQL queries.
  • Precision: Because it executes code against your database, the results (counts, sums, averages) are 100% accurate, not hallucinations.
  • Complex Logic: It can handle grouping, filtering, and cross-table references.
    • “Which product category had the highest growth rate QoverQ?”
    • “List customers who haven’t placed an order in the last 6 months but have a balance > 0.”

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2. Intelligent Visualization

Turn data into insights instantly. AI Chat chooses the best chart type for your data.
  • Supported Charts: Bar, Line, Pie, Scatter, Area, and more.
  • Interactive: You can refine the chart by chatting. “Switch to a stacked bar chart” or “Color code by region”.
  • Dashboarding: You can pin these generated charts to your dashboard (Coming Soon).

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3. Builder Agent

AI Chat acts as a co-pilot for setting up your workspace.
  • Automations: Describe a workflow, and AI will configure the triggers and actions.
    • “When a new lead arrives, send a welcome email and create a task for the sales team.”
  • App Generation: Transform tables into apps. For full customization, use the dedicated App Builder.
  • Scripting: For developers, it writes precise JavaScript code for specific column calculations or automation scripts.

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4. Multi-modal Knowledge Base (RAG)

Combine your structured table data with unstructured files.
  • Document Analysis: Upload PDFs, Excel files, or images.
  • Hybrid Search: Ask questions that require reading the document AND checking the database.
    • “Read this invoice (PDF) and match it with the record in the Orders table.”
    • “Summarize the contract terms and check if this client violates them based on their usage record.”
Get real-time information from the internet to enrich your analysis.
  • Live Data: Query stock prices, news, or public datasets.
  • Context Fusion: Combine web results with your table data for comprehensive answers.
    • “Compare our Q3 revenue with the industry average published online.”

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Best Practices

  • Be Specific: Instead of “Analyze data”, say “Analyze the sales trend compared to last year”.
  • Reference Fields: Use exact field names when possible (e.g., “Sort by ‘Created Time’”).
  • Iterate: If the result isn’t perfect, give follow-up instructions like “Change the chart color to blue” or “Filter out cancelled orders”.