CerevoIntel
Financial Workflow Optimization
Financial Workflow Optimization
We're not going to show you glossy case studies with made-up numbers. These are actual implementations we built for Vietnamese businesses between January 2024 and March 2025. Some worked brilliantly from day one. Others needed tweaking for weeks before they clicked.
What matters is they're all running right now, processing real transactions, and making someone's workday considerably less frustrating.
A textile manufacturer was manually reconciling payments in four different currencies. Their finance team spent about 12 hours each week just matching transactions. We built an automated system that handles the heavy lifting.
Seven locations, dozens of purchase requests weekly, and everything sitting in email threads. Managers were losing track of what they'd already approved. We created a centralized system that keeps everyone on the same page.
Their accounts payable team was drowning in paper invoices from suppliers. Data entry errors were creating payment delays and strained relationships. The automated extraction system handles most invoices without human intervention now.
Lan's logistics company tried implementing forecasting software twice before. Both times, the team stopped using it after a few months because it just didn't fit how they actually worked.
When we started in August 2024, we spent more time watching their existing process than talking about new tools. Turned out their forecasting challenges weren't about calculation complexity—they needed better collaboration between warehouse managers and finance.
"The difference this time was someone actually understood why the previous systems didn't stick. We're six months in and the team is still using it daily. That's a first for us."
Every business handles money differently. There's no template that works for everyone, but our process for understanding what you need stays pretty consistent.
We spend the first two weeks just watching how your team actually works. Not how the process manual says they should work—how they really do things when nobody's looking over their shoulder. The gap between those two is usually where the problems hide.
By week three, we're testing something functional with your actual transactions. It's rough around the edges, but it handles real scenarios. This catches problems that theoretical planning always misses—like that one supplier who sends invoices in a weird format nobody remembered to mention.
New systems fail when you flip a switch and expect everyone to adapt overnight. We run parallel systems for 4-6 weeks while your team gets comfortable. Some people pick it up in days. Others need more time. Both are fine—we adjust the training pace accordingly.
After three months of real-world use, patterns emerge. Maybe one feature everyone was excited about never gets used. Or a minor function becomes critical to daily operations. We adjust based on what actually happens, not what we thought would happen.