Crene offers a visual assumption‑layer platform that decomposes live investment theses into their underlying premises, enabling teams to review and update those assumptions before each portfolio‑manager, risk, or investment‑committee discussion. The tool maps each thesis into a structured network of nodes—showing hundreds of assumptions, shared themes, and scenario anchors—so users can track changes, assess model disagreement, and align on macro‑economic impacts such as AI productivity or fiscal stress.
Funding
Funding not disclosed
Founders
Product
Problem
Investment teams often maintain models, notes, and data feeds without a systematic record of the underlying assumptions that drive their live theses, making it difficult to track changes, identify disagreements, and know when a view needs to be revisited.
Solution
Crene offers an assumption‑mapping platform that converts each live investment thesis into an interactive, hierarchical map of its core premises. Users can decompose macro or sector views into structured assumptions—such as AI adoption rates, productivity pass‑through, capex efficiency, and GDP attribution—and link each to evidence, model outputs, and scenario variants. The system continuously scores resolvable questions, highlights model disagreement, and flags assumptions that have crossed predefined review thresholds. By preserving a time‑stamped record of assumptions, changes, and calibration scores, Crene enables portfolio managers, risk analysts, and investment committees to conduct transparent, weekly reviews before decision‑making meetings. The platform is accessible on desktop and mobile, providing both full relationship visualizations and an indexed view for quick navigation.
Target Audience
Primary users are institutional portfolio managers, risk officers, and investment committee members at asset managers, hedge funds, and sovereign wealth funds who need a structured, auditable view of the assumptions behind their investment theses.
Features
- Hierarchical assumption maps that break down any live thesis into granular, linked premises
- Real‑time tracking of model disagreement and assumption pressure across multiple scenarios
- Automated scoring of cleanly resolvable questions with tiered calibration disclosure
- Threshold‑based alerts that identify assumptions requiring owner review before meetings
- Mobile‑optimized index view for rapid inspection of public theses, shared themes, and live assumptions
- Versioned record keeping that preserves the evolution of assumptions, evidence, and calibration over time
- Integration of public and proprietary thesis maps to support collaborative review within investment teams