Crene gives consequential investment views a durable structure: assumptions, evidence, disagreement, decisions, and version history in one living record.
Investment teams have models, notes, data feeds, expert calls, and debate. What they often lack is a living record of the assumptions underneath the view.
Crene frames each thesis with a horizon, decomposes the conditions that would decide it, reassesses the view against evidence and disagreement, and preserves governed changes.
The aim is not to produce a trade trigger. It is to give a PM, risk, CIO, or investment committee a record of what the team believed, what changed, and why.
The system should remember what the team believed, why it believed it, and what changed.
Model disagreement, assumption pressure, and missing evidence should be surfaced before review, not buried after the fact.
Where outcomes resolve cleanly, Crene scores the record and shows the misses.
The record can show what a thesis depends on without pretending every structural relationship is a scored forecast.
Stephen spent seven years in institutional finance at Goldman Sachs and Crédit Agricole before teaching himself full-stack software engineering.
Crene grew out of a problem he saw in institutional decision making: teams could track prices, models, notes, and meetings, but the assumptions underneath a thesis were rarely preserved as a system. When the world changed, it was hard to see which part of the view had actually changed with it.
Stephen builds across the full Crene stack, from data collection and model scoring to backend infrastructure and frontend product surfaces.
I built Crene because investment teams have plenty of inputs but no durable system of record for the view itself. Crene is the product I wanted before a thesis review: a place to see what the view depends on, what changed, where disagreement sits, what requires a decision, and how that decision is preserved.

Crene is useful only if the record can be inspected. We publish what can be scored, separate structure from scored forecasts, and avoid claims the data cannot support.
Where outcomes resolve cleanly, Crene scores the record in tiers and includes the misses.
The record can show what a thesis depends on without treating every structural relationship as a scored forecast.
Crene does not claim to price tail events or the genuinely unmodelable.