{
  "id": "ext_123456789",
  "template_id": "tmpl_987654321",
  "status": "completed",
  "confidence": 0.92,  // Overall confidence score
  "created_at": "2023-05-15T14:30:00Z",
  "fields": {
    "invoice_number": {
      "value": "INV-2023-0042",
      "confidence": 0.98  // Per-field confidence
    },
    "invoice_date": {
      "value": "2023-05-10",
      "confidence": 0.95
    },
    "due_date": {
      "value": "2023-06-09",
      "confidence": 0.94
    },
    "total_amount": {
      "value": 1250.00,
      "confidence": 0.97
    }
  },
  "tables": {
    "line_items": {
      "rows": [
        {
          "description": {
            "value": "Professional Services - Web Development",
            "confidence": 0.96
          },
          "quantity": {
            "value": 10,
            "confidence": 0.99
          },
          "unit_price": {
            "value": 125.00,
            "confidence": 0.98
          },
          "amount": {
            "value": 1250.00,
            "confidence": 0.97
          }
        }
      ]
    }
  }
}

What are Extractions?

Extractions are automated processes that use AI to pull structured data from your documents based on defined Templates. They analyze document content, identify relevant information, and convert unstructured documents into structured data.

Supported Document Types

  • Spreadsheets - Excel files, CSV data, and other tabular formats
  • PDFs - Forms, invoices, statements, reports, and more
  • Images - Scanned documents, receipts, business cards, and photos

Create an Extraction in the Dashboard

  1. Navigate to the Extractions page.
  2. Click New Extraction.
  3. Upload your document or provide a file URL.
  4. Select an existing Template or create a new one.
  5. Click Upload to start the process.

Create an Extraction via API

  1. Upload a file with the /v2/extractions/upload endpoint
  2. Specify a template ID to determine how data is extracted

The API will return an extraction ID you can use to check the status and retrieve results:

Response
{
  "id": "ext_abcdef123456",
  "template_id": "tmpl_987654321",
  "file_name": "document.pdf",
  "status": "processing",
  "created_at": 1682366228
}

For more detailed API documentation, see the API Reference.

Retrieve Extraction Results

Once an Extraction has completed, you can access the data in several ways:

  • View in Dashboard - See extracted fields and tables in the TableFlow dashboard
  • Download Results - Export the data as JSON, CSV, or Excel files
  • API / Webhooks - Retrieve results programmatically using the TableFlow API

How Extractions Work

TableFlow’s AI extraction process involves several key steps:

  1. Document Analysis - AI analyzes the structure, layout, and content of your document
  2. Template Mapping - AI matches document content to your template fields and tables
  3. Data Extraction - AI extracts the relevant data based on context and positioning
  4. Validation - AI validates extracted data against rules in your template

Next Steps

After creating extractions, you can use TableFlow’s API to integrate the extracted data into your applications.

{
  "id": "ext_123456789",
  "template_id": "tmpl_987654321",
  "status": "completed",
  "confidence": 0.92,  // Overall confidence score
  "created_at": "2023-05-15T14:30:00Z",
  "fields": {
    "invoice_number": {
      "value": "INV-2023-0042",
      "confidence": 0.98  // Per-field confidence
    },
    "invoice_date": {
      "value": "2023-05-10",
      "confidence": 0.95
    },
    "due_date": {
      "value": "2023-06-09",
      "confidence": 0.94
    },
    "total_amount": {
      "value": 1250.00,
      "confidence": 0.97
    }
  },
  "tables": {
    "line_items": {
      "rows": [
        {
          "description": {
            "value": "Professional Services - Web Development",
            "confidence": 0.96
          },
          "quantity": {
            "value": 10,
            "confidence": 0.99
          },
          "unit_price": {
            "value": 125.00,
            "confidence": 0.98
          },
          "amount": {
            "value": 1250.00,
            "confidence": 0.97
          }
        }
      ]
    }
  }
}