Bespoke prediction models trained on your data - demand, claims volume, production, footfall, traffic. Built by the team behind our weather engine, and back-tested before you commit.
We join your history with our weather, market and socioeconomic data - and train a model for the one number your business runs on.
Sales, claims or production history joined with 20 years of weather and market context.
The prototype phase ends with numbers on held-out seasons - you see the accuracy first.
Demand, claims volume, footfall, output, occupancy, risk - if it has a pattern, it can be forecast.
Distributions and confidence, so you can plan on the risk level you choose.
API feeds, dashboards or scheduled reports - matched to how your team works.
Models keep learning with every season; we watch the accuracy so you don’t have to.
A season or two of history is usually enough to scope the model - under NDA, in any format.
A working model on held-out data within weeks - with honest accuracy numbers, not slides.
We run it as a service, or build it and hand it to your data team - your call.
You consume forecasts; we own the pipeline, monitoring and retraining.
We design, train and document the model - then hand it over with the playbook.
Usually one to two seasons of history. We’ll tell you quickly - and honestly - if it isn’t enough for a reliable model.
That’s what the prototype phase is for: you see back-test numbers against your baseline before committing to production.
Per agreement - from a service you subscribe to, up to full IP transfer with handover.
Processing runs under NDA and a data-processing agreement; your data is never used for other clients.
“The hardest part of a custom model isn’t the algorithm - it’s the data that has to surround it. We bring twenty years of it.”
Tell us what you’d like to predict and what history you have - we’ll scope a prototype and tell you honestly whether it’s worth building.
Discuss my use case