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As a company, the number of invoices and receipts you have to deal with often grows exponentially with your business activity.
While that’s good news on one end, it also means a lot of grunt work and precious human resources being spent on data entry. Which means it’s a beautiful use case for automation. And while we might think, “oh just use an OCR for that,” it turns out that invoices are so diverse in their formatting, that there’s a joke in the accounting community that “reading an invoice is harder than driving a car.”
Solving exactly this problem is Paperflow, the company of my new guest, Carsten Nørrevang (thankfully you can learn the right pronunciation of his Danish surname in the episode!) — and I learned some very interesting things through the discussion.
Here’s their value proposition in a nutshell: while most OCRs and data capture software can do generic tasks, training a specialized algorithm to read millions of types of invoices is extremely expensive. Carsten said they not only have a team of 30+ people solely dedicated to data preparation but have also built special tools to help mitigate this problem.
What I find really cool is that Paperflow is a really great example of how we can use AI to fix inefficiencies across the entire value chain of today’s businesses. Here’s what else you’ll find in this episode!
00:30 — What Paperflow does, and Carsten’s background as a former CFO
09:00 — Finance teams spend a surprising amount of time on document processing
11:30 — Why Paperflow is named, well… “paper flow”
14:00 — Solving the tough technical challenge of processing invoices
25:00 — The future roadmap: a smart document assistant
30:00 — Competitive landscape in document processing and data capture, and Paperflow’s approach
35:30 — Why banks in the Nordics are under pressure
40:00 — Paperflow’s fundraising journey
44:30 — Carsten’s perspective on going public
(Ethics Policy: These opinions are 100% my own as an independent observer and educator. I don’t own stock in guests’ companies or their competitors, nor do I get paid by them in any form for any reason at the time of publishing, unless specifically stated. Episodes are also not intended to be an automatic endorsement of any company or its products and services.)