One of the main issues with AI document parsing is that because no solution is 100% accuracy, it's hard to tell if a given page is parsed incorrectly: for instance a misaligned table, missing/hallucinated values, or messy scans

over the past few months we've invested a lot in models that provide more calibrated confidence scores - it will give you a confidence level that the page is parsed correctly. it is correlated with the parsing mode and how complex the source page is.

this allows you to bake in human-in-the-loop mechanisms where you can review and correct the outputs, or trigger automated fallback logic, for highly sensitive paperwork-heavy processes.

come check out our high-effort scores! developers.llamaindex.ai/lla…

Come sign up to LlamaParse here: cloud.llamaindex.ai/

LlamaIndex 🦙 (@llama_index)
confidence scores in LlamaParse just got an upgrade 🦸‍♀️

our new high-effort mode provides granular page-level scores with text explanations to help you intimately understand parsing quality of your documents. we even refer back to the original document for an extra check when generating the score.

use high-effort only when you need it, at 5 additional credits per page.

try it on your docs: developers.llamaindex.ai/lla…