what AI API should I use for document classification

For document classification, the best AI API depends on what kind of documents you have and how much control you need. Here are the main options:

Good choices

1. OpenAI API

Best if you want:

• High-quality text understanding
• Classification from raw text or extracted document text
• Fast setup with few examples

Use it when your task is like:

• “Classify this contract as NDA / MSA / SOW”
• “Route this email/invoice/support ticket to a category”
• “Detect document type from text”

Why:

• Very strong general language understanding
• Easy to use with structured outputs / function calling
• Good for few-shot or zero-shot classification

2. Google Cloud Document AI

Best if you need:

• Document parsing + classification
• OCR and layout-aware document processing
• Enterprise document workflows

Use it when:

• You have PDFs/scans/forms
• You need structured extraction plus classification
• You want a managed document pipeline

3. AWS Textract + Bedrock

Best if:

• You’re already on AWS
• You need OCR/extraction from scans
• You want to combine extraction with a model from Bedrock for classification

4. Azure AI Document Intelligence

Best if:

• You use Microsoft/Azure stack
• You need OCR, layout extraction, and custom document models

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Practical recommendation

If your goal is just classification, I’d usually recommend:

Use OpenAI API if:

• You already have the text
• You want the simplest integration
• You need flexible classification logic

Use Google/Azure/AWS document services if:

• You need OCR or layout extraction first
• Your documents are scanned or heavily formatted

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Simple decision guide

• Text-only documents → OpenAI API
• Scanned PDFs/images → Document AI / Textract / Azure Document Intelligence
• Need both extraction and classification → cloud document platform + LLM
• Need custom domain accuracy at scale → train a custom classifier or use embeddings + classifier

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One more option: embeddings + lightweight classifier

If you have lots of labeled examples and fixed categories, you can:

• Convert documents to embeddings
• Train a small classifier or use nearest-neighbor matching

This is often cheaper and very effective for stable taxonomies.

If you want, I can recommend the best API specifically for your document type if you tell me:

1. whether the docs are PDFs, scans, emails, etc.
2. how many categories you have
3. whether you need OCR/extraction or only classification