Hey everyone,

I'm working on an application that uses AI to extract structured data from commercial documents - invoices, contracts, purchase orders, that kind of stuff. I've been testing Claude and Google's multimodal models and they work really well for this use case.

However, I need to evaluate what Azure offers since that's our cloud environment or what other options could be considered. After digging into it, I found there are basically two main paths:

1. Azure Document Intelligence (formerly Form Recognizer)

This is their dedicated document processing service. It has prebuilt models for invoices, receipts, contracts, tax forms, etc. Pricing is around $10/1,000 pages for prebuilt models, $30/1,000 for custom extraction. Seems very accurate for structured documents and returns proper JSON with confidence scores and bounding boxes.

2. Azure OpenAI with GPT-4o Vision

Send document images directly to GPT-4o, use prompt engineering to define extraction schema, and use Structured Outputs for guaranteed JSON compliance. More flexible but apparently more expensive (~$0.05-0.07/page) and potentially less accurate on complex tables.

3. Hybrid approach

Microsoft's own samples show using Document Intelligence Layout model to convert PDFs to Markdown first, then feeding that to GPT-4o for the actual extraction. Supposedly gives you the best of both worlds - accurate OCR + flexible schema extraction.

My questions for those who've built similar systems:

• If you're using Azure, which approach did you go with? How's the accuracy and cost working out in production?

• For those using Document Intelligence prebuilt models - how well do they handle non-standard invoice formats or documents in multiple languages? Do you end up needing custom models anyway?

• Anyone tried the hybrid approach (Doc Intelligence + GPT-4o)? Is the added complexity worth it vs just using GPT-4o directly on images?

• How does Azure Document Intelligence compare to Claude or Google Document AI in your experience? I've had good results with Claude's vision capabilities but wondering if a specialized service like Document Intelligence would be more reliable at scale.

• For high volume processing (let's say 50k+ pages/month) - what's been most cost-effective?

• Any gotchas or lessons learned you wish you knew before starting?

Would really appreciate hearing about real-world experiences. Most of what I've found is marketing material or basic tutorials, not much on how these solutions hold up in production with messy real-world documents.

Thanks!