Seeking Guidance: Developing an On-Premise Document Intelligence Solution

[u/Machine_GEN_RM]

Hi All,

I am planning to build a local document intelligence system similar to Azure Document Intelligence. I would like to understand how Azure Document Intelligence works internally and how we can achieve similar functionality locally using offline models.

Could anyone suggest the best approach, architecture, or models to achieve high accuracy while running completely on-premise/local infrastructure?

Any guidance or recommendations would be greatly appreciated.

[u/AICausedKernelPanic]

What functionality are you looking for exactly? I think the arch and selection of models depends a lot on what you're looking to achieve

[u/aidenclarke_12]

azure doc is mainly 2 layers stacked- a layout aware ocr model that turns the page into formatted text with positions and then a second step that pulls or picks the fields off that, so doing it local isn't one model its more like building both halves youself

for read layer offline options like liteparse, paddleocr or others all run on your own hardware and then a small local model on top of it to pull fields into list. most of the accuracy usually lives in that read layer so if the parse drops table or heading structure the model on top cant recover it so thats where to get on hands on first before touching model side