Crene turns one live market view into a weekly review surface. Assumptions, model disagreement, and rethink triggers before the next PM, risk, or IC discussion.
The map starts with a live AI thesis and shows the assumptions underneath it: enterprise adoption, productivity pass through, capex efficiency, labor substitution, margin evidence, and GDP measurement.
The desktop map shows the full relationship view. On mobile, Crene shows the same structure as an index: public theses, shared assumption themes, and the live assumptions attached to each map.
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10 shared assumption threads connect the live theses. Markets, AI labor, AI productivity, rates, fiscal capacity, growth poles, dollar system, AI content, inflation, and demographics. Interactive graph on desktop.
View full example →The live map is proof of the method. The pilot is the product workflow. Use the public example to see how Crene structures one debated macro thesis, then submit a thesis your own team needs to review.
Crene should make a team feel the Monday meeting rhythm: what moved, where the thesis is fragile, and what would force a rethink before the next IC, risk review, or strategy meeting.
A single map clarifies one decision. The weekly review cadence is what records how a team updates judgment over time.
Start with one live market view where the evidence has gotten messier. Crene turns it into assumptions, disagreement, rethink triggers, and weekly changes your team can review before the next meeting.
Explore public examples of thesis, factor, and scenario views behind Crene's private review workflow.
All examples →Will the United States account for more than 30% of global nominal GDP by 2050?
What determines whether AI expands, reduces, or restructures productive work in the United States by 2030?
Does India become a durable third pole of global growth, capital formation, and technology demand by 2035?
Can Europe convert threat perception into durable fiscal, industrial, and military capacity by 2030?
Resolved scoring is reported separately from still-accruing product maps.
Binary questions broken into observable components, model consensus, disagreement, and resolution criteria.
All thesis maps →Whether the Warsh Fed converts its hawkish June pivot into an actual 2026 rate hike. 100 child conditions spanning policy path, Fed communications, inflation, labor resilience, institutional reset, market pricing, and consensus narrative.
Whether realized enterprise AI absorption lags infrastructure investment. Nine weighted settlement indicators across six causal domains, plus 100 supporting children.
Will AI generated content exceed human generated content on the US internet before 2030? 100 child situations spanning platform dynamics, search and SEO, journalism, video and visual content, academic integrity, authentication infrastructure, economic disruption, legal frameworks, societal trust, and compute infrastructure.
Numerical variables decomposed into drivers, percentile distributions, model spread, and update trajectories.
All factor maps →What percentage of US GDP will be directly attributable to AI systems by 2030?
What will the S&P 500 Index (SPX) official close be on the final trading day of 2026?
What will the US 10-year Treasury constant maturity yield be at the last Treasury market close of 2026?
Crene is designed for teams that need inspectable assumptions, model disagreement, and update conditions before evidence is complete.
Crene maps one investment thesis your team is already debating, then tracks the assumptions, model disagreement, and update conditions over time.
Review a thesisPublic read endpoints for the proof layer. Private review customers get scoped write access around one live thesis.
API documentationBuilt by Stephen Lee. Seven years in institutional finance at Goldman Sachs and Credit Agricole, now building Crene for investment teams reviewing strategic theses.
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