#12 - Building Reliable Document AI Pipelines - Pierre-Louis Bonvin

I talk with Pierre-Louis Bonvin who is a Solutions Engineer at Apryse  and we talk about how to get better results from document AI by focusing on input quality and designing a full processing pipeline: capture, preprocess, OCR, smart extraction, and then LLMs as the last step.

Improving preprocessing and structured extraction speeds up processing, reduces token costs and privacy exposure, and dramatically increases accuracy when scaling to thousands or millions of documents. Pierre also talks about the biggest mistakes that companies do when seting up their document AI pipeline and the difference in API token costs.