Built on Real Business Frustration
We started Vipwave Prismo because spreadsheet forecasting was driving us crazy. Henrik had spent fifteen years watching companies make guesses instead of decisions. Most forecasting tools either cost too much or required a finance degree to understand.
The truth is, small and mid-sized businesses need the same data-driven insights that big corporations have. But they need it without hiring three analysts or spending six months on implementation.
So we built something different. Our system learns your business patterns and gives you actual forecasts you can work with. Not perfect predictions, but realistic scenarios that help you plan better and waste less time second-guessing yourself.
Why We Do This Work
Financial planning shouldn't feel like archaeology. You shouldn't need to dig through last quarter's data for three hours just to make one budget decision.
We believe businesses deserve forecasting that adapts to their reality, not the other way around. Your seasonal patterns matter. Your growth trajectory matters. Your actual cash flow timing matters more than theoretical models.
How We're Different
Most forecasting systems force you into their framework. We've seen companies spend months customizing software that still doesn't match how they actually work.
Our approach flips that around. The system watches your data patterns and adjusts its predictions based on your specific business behavior. It's smarter forecasting that gets better the longer you use it.
How Our System Actually Works
Pattern Recognition
The system starts by analyzing your historical data to identify trends, seasonality, and anomalies. It looks at revenue cycles, expense patterns, and cash flow timing to build a baseline understanding.
Adaptive Forecasting
Based on those patterns, it generates multiple scenario forecasts that reflect different growth trajectories and market conditions. These aren't wild guesses but probability-weighted predictions that evolve as new data comes in.
Continuous Learning
Every month, the system compares its predictions to actual results and adjusts its algorithms accordingly. This means your forecasts become more accurate over time as the AI learns what really drives your numbers.
We were spending two full days each month building budget forecasts in Excel. Now I get scenario analysis in about twenty minutes, and honestly, the predictions are more reliable than what we were doing manually.
Saskia Veltman
Finance Director, Regional Distributor
