Doc AI Unclogs Pharma’s AP Bottleneck

Amara Lawson

Hey y’all, welcome back to Deep Dive 360! I’m Amara, and as always, I’ve got Ravi Kumar with me. Ravi, how’s it going?

Ravi Kumar

Hey Amara, doing well! Excited for this one—because, honestly, pharma AP is one of those topics that sounds boring until you’re in the thick of it, and then it’s just chaos.

Amara Lawson

Right? I mean, we’ve talked about AI in research and manufacturing before, but invoice processing in pharma and biotech is a whole different beast. You’ve got suppliers from all over—big, small, local, global—and every single one sends invoices in their own special flavor. No EDI standard, no neat templates, just a mess of PDFs, Excel files, even photos of paper invoices. I remember this one sourcing project—oh, it was a nightmare. We were launching a new product line, and the supplier paperwork was so all over the place, we almost missed our go-live date. I’m not exaggerating, it was that bad.

Ravi Kumar

Yeah, and it’s not just the formats, right? The AP team has to manually extract all the details—vendor name, invoice number, dates, totals. Then they have to match every line item to the purchase order, do a three-way match with the goods receipt, and validate quantities, prices, part numbers. And this is before anything even gets into the ERP for payment. It’s repetitive, it’s slow, and it’s so easy to make mistakes. And in pharma, you can’t just shrug off a mistake. GxP compliance means you need a full audit trail, and you can’t just trust the vendor’s invoice. If you pay the wrong invoice, you could be out real money—or worse, you could be out of compliance.

Amara Lawson

Exactly. And I think that’s what makes pharma so much harder than, say, automotive or consumer goods. The stakes are just higher. You’ve got to be right, every single time. And the volume—thousands of invoices a month, all in different formats. It’s no wonder AP teams get buried. I mean, I’ve seen teams literally burn out trying to keep up.

Ravi Kumar

And it’s not just burnout, it’s risk. If you’re manually keying in 50-line invoices, you’re gonna miss something eventually. Or you’re gonna spend all your time double-checking, and nothing else gets done. It’s a lose-lose.

Amara Lawson

And then there’s the fraud angle. I mean, let’s be real—fraud happens. Vendors slip in extra line items that aren’t on the PO, or they use part numbers that look almost right but aren’t. Sometimes it’s just a typo, but sometimes it’s not. And if you’re tired or rushing, you might not catch it.

Ravi Kumar

Yeah, and I’ve seen it firsthand. Back in the early days at Aekam AI, we were working with a client who kept getting these invoices with part numbers that were just slightly off—like, one digit different from their actual SKUs. At first, nobody noticed, because it looked legit. But when we ran the data through our system, it flagged those lines. Turns out, the vendor was billing for items they didn’t even supply. It wasn’t a huge amount, but it could’ve added up over time. And in pharma, with GxP compliance, you need to be able to show exactly what you paid for, when, and why. If you can’t, you’re opening yourself up to audit findings, or worse.

Amara Lawson

That’s the thing—compliance isn’t just a box to check. It’s about protecting the business. If you can’t prove your controls work, you’re at risk for fines, or even losing your license. And the fraud isn’t always obvious. Sometimes it’s just a few extra units here or there, or a line item that looks like it belongs. How do you even spot that without burning out your team?

Ravi Kumar

Honestly, you can’t, not at scale. That’s why automation is so important. You need something that can check every line, every time, and flag anything that doesn’t match your master data. Otherwise, you’re just hoping for the best. And hope is not a strategy, especially in regulated industries.

Amara Lawson

So let’s talk about what happens when you actually automate this stuff. You worked with a global pharma company, right? What did that look like?

Ravi Kumar

Yeah, this was a big one—hundreds of vendors, invoices in every format you can imagine, different currencies, scanned PDFs, Excel, Word, you name it. Their AP team was spending 7 to 10 minutes per invoice, just extracting data and validating it against their item library before entering it into SAP. And that’s not even counting the time spent chasing down errors or investigating fraud.

Amara Lawson

That’s wild. Thousands of invoices a month, all by hand. I can’t even imagine.

Ravi Kumar

It was a nightmare. So what we did was build a custom DocAI integration for them. Not just a generic tool, but something trained on their actual invoice formats, connected to their ERP, and matched to their part number library. DocAI would extract all the header details and every line item, automatically match part numbers to their internal SKUs, and flag anything that didn’t match. Then it would clean, structure, and validate the data, and feed it straight into SAP—ready for payment approval, with a full audit trail.

Amara Lawson

So the AP team wasn’t typing in every invoice anymore—they were just reviewing the ones that got flagged?

Ravi Kumar

Exactly. They moved to an exception-based workflow. Instead of spending all day on data entry, they focused on the 5% of invoices that actually needed human review. Fraud detection was automated, and their cycle time per invoice dropped from about 10 minutes to under a minute. Plus, they had a clear audit trail for compliance. It was a total game-changer.

Amara Lawson

That’s huge. And I love that it wasn’t just “here’s another app, go log in.” It was a real solution, built for their workflow. I wonder—do you think this kind of exception-based review could work in automotive supply chains? I mean, we’ve got a lot of the same problems: tons of suppliers, weird invoice formats, compliance headaches…

Ravi Kumar

I think it could, but you’d have to tailor it. Automotive has its own quirks—like, the part numbering systems are different, and the compliance requirements aren’t always as strict as pharma. But the core idea—automate the grunt work, flag the exceptions, and let people focus on what matters—that’s universal. You just have to build the integration for the specific industry. Generic tools don’t cut it.

Amara Lawson

Yeah, and as we talked about in our last episode, it’s about empowering people, not replacing them. Let the AI handle the repetitive stuff, and let your team focus on the tricky cases. That’s how you get real value. Well, I think that’s a good place to wrap for today. Ravi, thanks for sharing your stories—and thanks to everyone listening. We’ll be back soon with more deep dives into how AI is transforming the real world. Take care, y’all!

Ravi Kumar

Thanks Amara, always a pleasure. And thanks to everyone for tuning in. See you next time on Deep Dive 360!