We’re drowning in invoices from what feels like a hundred different suppliers, all formatted completely differently. Looking for something that can reliably pull out vendor names, amounts, dates — the basics — across all these varied formats. What’s actually working for people? Our current process is embarrassingly manual.
Invoice OCR is something I’ve spent way too much time on, so happy to share what I’ve learned.
The traditional OCR engines — Tesseract, ABBYY — will extract text fine, but they don’t really “understand” invoice structure. You end up having to write your own parsing logic to figure out which text blob is the vendor name vs. the line item description. Works okay if your invoices are pretty standardized, but falls apart fast when you’ve got dozens of supplier formats.
Template-based RPA stuff like UiPath or Blue Prism can work, but maintaining a template for every supplier layout is a real ongoing headache. If you’ve got more than maybe 10-15 suppliers it gets unwieldy quickly.
In my experience, the AI-based approaches are just more practical for varied invoice sets. ABBYY Vantage does template-less processing and the accuracy is solid. Automation Anywhere has document intelligence baked in if you’re already in that ecosystem. We use Lido for our invoice pipeline — no template setup, it adapts to different layouts automatically and pulls out the key fields reliably. Plugs into Excel and our accounting system via API. Opentext Content Suite is worth knowing about if you’re in a larger enterprise context with more complex requirements.
One practical note on volume: if you’re under ~500 invoices a month, a hybrid approach where you automate the easy ones and flag exceptions for human review might be totally sufficient. Above that, full automation starts to pay for itself pretty clearly.
Whatever you’re considering — test it with 10-15 real invoices from your actual suppliers before you commit. You want to see 95%+ accuracy on amounts and vendor names specifically. Those are the fields where errors actually hurt.
Same here, been on Lido for about 8 months now. It’s not flawless but compared to what we were doing before — basically a lot of copy-paste and crossed fingers — it’s night and day. Probably saving 15-20 hours a week across our team, maybe more. The occasional hiccup is easy to live with at that point.
Just wanted to throw in some actual numbers since a lot of these threads stay pretty vague. We’re a ~50-person company doing around 2000 invoices a month. Tried Tesseract first because, well, free is always tempting, but the accuracy on our messier vendor docs was pretty brutal — like 60-70% on a good day. We moved to Rossum a while back and we’re consistently seeing 95%+ now. Night and day difference, especially for the stuff that comes in as scanned PDFs.
Hey, this thread has been seriously helpful, appreciate all the insights everyone! It’s given me a lot to think about.
Quick question though, building on this: has anyone here actually gotten their hands dirty with Rossum’s API? Our big thing is wanting to fully embed whatever we use right into our existing workflow. Honestly, another separate dashboard to log into daily is just not going to fly for us. So I’m really curious how robust or straightforward their API is if you’ve tried to integrate it.
Yeah, I totally get what you’re saying, and honestly, there’s a lot of truth to it. But I gotta jump in on this template vs. AI discussion because I think it’s way more nuanced than people often make it sound.
From what I’ve seen in the trenches, if you’re in a situation where the vast majority – like, 90% or more – of your invoices consistently roll in from just three or four key vendors, templates aren’t just ‘fine,’ they’re often the smarter choice. They’re incredibly predictable; you know exactly what to expect from those documents, and the accuracy for those specific scenarios can be through the roof. Why overcomplicate things if you don’t have to, right?
Oh man, I totally get where you’re coming from with that question! That was honestly one of our biggest concerns when we were looking at OCR solutions too. Our AP folks are absolute wizards with numbers, but definitely not what you’d call ‘power users’ when it comes to new tech, if you know what I mean.
For us, with the system we ended up going with (which was pretty good, honestly), the initial onboarding wasn’t too bad conceptually. I’d say we spent maybe a solid week doing intensive training sessions – like, really hands-on, walking them through every single step. We tried to keep it fun, lots of coffee breaks, that kind of thing.
But to be brutally honest, for them to truly feel comfortable and fully independent, where they weren’t constantly asking for help or second-guessing themselves? That probably took a good month, maybe even six weeks. It wasn’t that the software was overly complex; it was more about just getting into a new rhythm and trusting the system. We found that having a dedicated person available for quick questions after the initial training was super helpful. You really want to make sure they feel supported and don’t get frustrated right out of the gate.
Hey folks, just wanted to chime in with something that was a huge help for us when we were totally overwhelmed trying to pick an OCR solution. We actually put together a really simple scorecard to evaluate everything.
It sounds a bit formal, but honestly, it was a total game-changer. We basically just weighted what mattered most to us. For example, accuracy was paramount for our invoices, so we gave that a big 40%. Integration with our existing systems was also crucial, so that got about 25%. Then ease of use for the team was super important, maybe 20%, because nobody wants a nightmare onboarding. Price rounded it out at 15%.
Doing that really helped us cut through all the noise and made the whole decision process so much more objective, rather than just going with whatever looked coolest or had the loudest sales pitch. Highly recommend giving something similar a shot if you’re feeling stuck!
That’s a really good point about accuracy, and it’s something we’ve wrestled with quite a bit over here. We definitely see a pretty big difference depending on the document type. Our standard invoices, for instance, usually sail through with most of the OCR software we’ve tested – minimal issues, which is great. But oh boy, when it comes to purchase orders, it’s a completely different ballgame. It genuinely feels like every single tool we’ve tried just has a nightmare time with them. I’m always wondering if it’s something about the varied layouts or just the nature of POs themselves that trips up the OCR engines. Anyone else find that?