We Help You See Around Corners
Financial decisions feel heavy because you're betting on an uncertain future. We built fluxis-firely because we got tired of watching businesses make critical choices based on gut feeling and spreadsheet guesses.
How This Started
Back in 2019, I was consulting for a manufacturing company in Taichung. They wanted to expand into Southeast Asia but couldn't get a straight answer about whether it made financial sense. Their CFO had three different Excel models, each telling a different story.
That's when it clicked. Businesses don't need another forecasting tool—they need a way to test their assumptions before committing resources. What happens if supplier costs jump 15%? What if that new market takes eighteen months to penetrate instead of twelve?
We started building models that let decision-makers play out different versions of reality. Not predictions. Just better preparation.
Our Approach to Modeling
Question First, Model Second
Most people start with data. We start with the actual decision you're trying to make. What keeps you up at night? That's where the model begins.
Multiple Futures, Not One
Single-point forecasts are basically fiction. We build scenarios that show you a range of possibilities—optimistic, realistic, and the version where Murphy's Law kicks in.
Built for Change
Your assumptions will shift. Markets move. We design models you can adjust as new information comes in, not static documents that gather digital dust.
What Drives Our Work
These aren't corporate values we printed on a poster. They're the principles that shape every model we build and every conversation we have.
Honest Limits
We tell you what the model can't answer. Clarity about uncertainty is more valuable than false precision.
Real Complexity
Business isn't simple, so we don't pretend your decisions are either. But we make complexity manageable.
Your Context
Taiwan's market has specific dynamics. We build that local knowledge into every scenario we construct.
Practical Output
If you can't use it to make a decision, we haven't done our job. Models exist to clarify choices.
Who's Behind the Models
Small team, deliberate approach. We'd rather work with fewer clients and do it properly than scale up and lose the nuance that makes scenario modeling actually useful.
Silje Rustad
Silje came to Taiwan in 2017 after working in risk analysis for Nordic energy companies. She got frustrated with traditional forecasting methods that treated uncertainty like a bug instead of a feature.
Now she builds models that embrace complexity. Her background in actuarial science means she thinks in probabilities, not certainties. Clients appreciate that she explains technical concepts without the jargon fog.