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What is DeepTagger?

DeepTagger is an AI-powered document intelligence platform that automatically extracts structured data from documents.

The Problem

Manual data entry from documents is: - ⏱️ Time-consuming - 💸 Expensive - ❌ Error-prone - 📈 Not scalable

The Solution

DeepTagger uses machine learning to automate extraction:

  1. Annotate a few example documents (3-5)
  2. Train the AI to understand your document structure
  3. Extract data from new documents automatically
  4. Validate and improve with corrections

How It Works

1. Document Upload

Upload documents in various formats: - PDF files - Images (JPG, PNG, TIFF) - Scanned documents - Text files

2. Annotation (Training)

Select text in example documents and label what it represents: - Invoice numbers - Dates - Amounts - Custom fields

3. ML Training

DeepTagger learns patterns: - Where fields appear - How they're formatted - Context and relationships - Variations in layout

4. Automatic Extraction

New documents are processed automatically: - AI predicts field locations - Extracts structured data - Returns JSON output - Confidence scores included

Use Cases

Invoice Processing

Extract invoice numbers, dates, totals, line items → Send to accounting system

Receipt Management

Parse receipts → Log expenses → Submit for reimbursement

Form Processing

Extract structured fields from unstructured text forms → Create database records

Contract Analysis

Identify parties, dates, terms, obligations → Alert legal team

Document Archival

Extract metadata from any document → Searchable archive

Key Benefits

  • 🚀 Fast: Seconds per document
  • 🎯 Accurate: 95%+ accuracy with proper training
  • 🔄 Scalable: Process thousands of documents
  • 🔌 Easy Integration: n8n node or REST API
  • 💰 Cost-Effective: Reduce manual labor

Getting Started

  1. Create account (free tier available)
  2. Set up n8n integration (recommended)
  3. Create your first project
  4. Train with examples
  5. Automate your workflows!

Technical Architecture

DeepTagger combines: - Computer Vision - Document layout understanding - Natural Language Processing - Text comprehension - Machine Learning - Pattern recognition - Few-Shot Learning - Learn from minimal examples

The result: Powerful document intelligence without massive training datasets.

Next Steps