How forecasting became clearer
We started with a simple question: can business predictions be more than guesswork?
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What we learned from failed predictions
Zliptron emerged in 2023 after watching too many businesses make decisions based on outdated assumptions. The gap between what companies thought would happen and what actually did was often wide enough to derail entire strategies.
We noticed something consistent: the tools existed, but the approach was scattered. Data sat in different systems. Assumptions went unchallenged. Forecasts were built once and forgotten until they proved wrong.
Our method focuses on iterative refinement rather than one-time projections. Models get updated as new information arrives. Assumptions are documented and revisited. The goal is not perfect accuracy but better-informed decisions over time.
Where we stand now
The people behind the forecasts
Siobhán Ó Dálaigh
Lead Analyst
Siobhán spent eight years building predictive models for retail and manufacturing before joining us. She focuses on identifying which variables actually matter and which ones just add noise to the equation.
