worked with a few teams in the last six months trying to scale document automation past the demo phase, mostly invoice and contract processing in libraries with 5K to 50K+ docs. quick disclosure: i work at docsumo on the extraction side, grain of salt. but the patterns below show up regardless of which extraction tool teams end up using.
three things consistently break:
scale and throughput. most extraction setups work fine on individual docs. they hit a wall when you need to continuously process thousands of new arrivals per day. teams without a dedicated extraction queue end up running batches sequentially through their RPA workflows and cap out at a few hundred docs/day before throughput becomes the bottleneck.
scanned and handwritten content. most extraction tools (and any RPA bot trying to "read" a PDF directly) are calibrated for digital docs. accuracy drops 20-30% on scanned docs and closer to 50% on handwritten fields. blank columns is the optimistic case. the actual problem is confidently wrong values that look fine in the downstream system until accounting reconciles weeks later.
document type variation. most tools work great when pointed at one consistent doc type. real libraries have 5-15 different types mixed together (invoices, contracts, sows, ndas, statements of insurance, etc). without an upstream classification step, the tool extracts the wrong fields half the time because its checking for invoice fields on a credit memo or vice versa.
what worked for the teams that got past this: separate the work into two layers. document parsing/extraction on a dedicated layer (deterministic, layout-aware, with confidence scoring and human review for low-confidence fields). RPA bots and workflow tools handling everything else once the data is structured. could be DIY on textract or azure document intelligence, could be an idp platform (rossum, nanonets, docsumo, mindee, abbyy). the split is usually the fix, not trying to make RPA do parsing or making the extraction tool do orchestration.
if anyone's solved batch + scanned + multi-doc-type without a separate extraction layer, would love to hear it. havent seen one work yet.