Sentintell weighs the forecast against your cost of acting and loss of not acting, and returns one call you can defend — backed by the historical record, not a black box.
You define the economic stakes. Sentintell calculates whether the forecast justifies acting.
Region, variable, threshold, forecast day — plus your cost of acting (C) and loss if you don't (L).
A 31-member GEFS ensemble computes the calibrated probability your threshold is crossed.
The Murphy–Richardson framework weighs that probability against your C/L ratio for expected value.
One call — ACT or DO NOT ACT — its dollar value, and the historical record that stands behind it.
Not a probability or a range — a single actionable call, with the financial reasoning that produced it laid out in full. The forecast is the input; the decision is the product.
You set the cost of acting and the loss of not acting. The threshold adapts to your business, not a generic rule.
Every call exposes the probability, the historical reliability at that probability, and the matching past cases.
When a forecast falls outside the historical record, the system says so — instead of dressing up a guess.
Define a point or draw a polygon; analyse temperature, precipitation or wind at the threshold that matters to you.
Wherever a weather event forces a yes/no choice — spend to protect, or accept the exposure — and both sides can be put in currency.
For vineyards, orchards and other high-value perennial crops, protection is cheap and known; a lost crop is catastrophic. That asymmetry is exactly where a calibrated forecast is worth the most — and what Sentintell quantifies.
This is about protecting operations, not speculating on markets. When a low-wind cold spell or demand swing is forecast, Sentintell tells a generator, utility or operator whether the signal justifies hedging exposure or pre-positioning resources — and what the call is worth.
Insurers and risk teams already think in cost-and-loss terms. Sentintell expresses weather risk the same way: the probability of a threshold event, its calibrated reliability, and the value of acting — for advisory, mitigation and parametric design.
A PhD atmospheric scientist and university researcher in ensemble weather forecasting, Barry is the technical lead behind the Sentintell engine. The methodology is built on peer-reviewed forecast-verification science — the discipline that evaluates whether a forecast is genuinely skilful — applied to whether it's economically worth acting on.
Sentintell is a product of AgriMetra Ltd. (Israel).
Sentintell is early by design. Rather than sell a self-serve plan, we partner directly with a handful of operators — modelling decisions on their real cost and loss numbers, proving the value, then shaping pricing around what works.
No fake metrics. No customer logos we haven't earned. Just the method, working on your numbers — and an honest account of what it can and can't do yet.
Bring a real weather-driven decision. In a short working session we'll model it live — region, threshold, your cost and loss — and show you the call with its evidence.
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