Built to be judged.
Every recommendation freezes its expected outcome before you act. When the world settles it, the outcome is recorded against the frozen expectation — and the ledger is what your agent answers to.
Request a briefingA forecast is a claim, not an opinion
Anyone can be confident. We made Cascadian falsifiable on purpose — a closed loop that turns every settled event into a score, and every score into a proposed update a human signs off on.
Claim
Every recommendation freezes its expected outcome before you act — a falsifiable claim on a specific event the world will eventually settle.
Resolve
When the event settles, the measured outcome is recorded against the frozen expectation. No edits. No excuses. The ledger is append-only.
Score
Each resolved claim is scored with a Brier score, and calibration is recomputed across the whole book — what we said vs. what happened.
Compound
Variance is diagnosed and a learning update is proposed — a human approves it — so the next decision's context is smarter. Nothing self-corrects.
Every forecast, scored in the open
No cherry-picking. The full book is published — wins, misses, and everything still unresolved — so the record can be audited, not pitched.
ILLUSTRATIVE — the public ledger populates as alpha decisions resolve. The rows below show the shape of the record, not measured accuracy.
| Question | Forecast | Resolves | Outcome | Brier |
|---|---|---|---|---|
| P(export-control escalation on advanced compute by Q3) | 0.62 | 2026-09-30 | Did not occur | 0.38 |
| P(a major cloud provider cuts inference pricing >25% in H1) | 0.41 | 2026-06-30 | Did not occur | 0.17 |
| P(USD/EUR closes below 1.05 at month end) | 0.28 | 2026-05-31 | Did not occur | 0.08 |
| P(Cascade-region grid demand sets a new summer peak) | 0.71 | 2026-08-31 | Did not occur | 0.50 |
| P(supplier lead times for a tracked component exceed 12 wks) | 0.55 | 2026-07-15 | Occurred | 0.20 |
| P(a tracked counterparty's default risk crosses threshold) | 0.34 | 2026-10-01 | — open — | — |
Brier score measures the squared error between a probabilistic forecast and the binary outcome — lower is better, 0 is perfect. We publish it per forecast and in aggregate. No single headline number stands in for the record.
Calibration, not confidence, is the whole game
A calibrated forecaster who says 70% is right 70% of the time. Plot forecast probability against realized frequency: the closer the points hug the diagonal, the more the numbers mean exactly what they say.
Confidence is cheap. A model can be loud and wrong. Calibration asks the only question that matters: when we say 70%, does it happen 70% of the time?
We track the full reliability curve, not a single accuracy stat — and we publish where we are over- and under-confident. A forecaster that knows the limits of its own certainty is worth more than one that is merely loud.
An agent inherits the trust of its inputs. Feed it an uncalibrated forecast and you have not given it intelligence — you have given it a liability that compounds with every decision it makes on your behalf. A scored, public ledger is the only honest basis for letting an agent act before money moves: not a promise of accuracy, but a record of it, open to anyone willing to check the math.
Judge it against your own book.
Bring the questions that move your business. We will show you the ledger, the scoring, and exactly how a frozen expectation is scored against what actually happened.
Request a briefing →