Transparent assumptions
Inputs, overrides, and model drivers are surfaced clearly so users can inspect the logic behind a valuation.
About astrys.ai
Making institutional-quality valuation more accessible, transparent, and explainable.
astrys.ai is a modern valuation platform for fundamental investors, analysts, students, and founders who want clearer assumptions, explainable models, and better investment research workflows.
Why We Exist
Modernizing valuation without turning it into a black box.
Traditional valuation workflows are often spreadsheet-heavy, difficult to audit, expensive, or designed primarily for large institutions. astrys.ai aims to modernize valuation without turning it into a black box.
- Spreadsheet-heavy workflows
- Difficult-to-audit assumptions
- Expensive professional tools
- Limited explainability
- Manual scenario analysis
What Makes astrys.ai Different
Purpose-built for transparent investment research.
Explainable models
Valuation outputs are connected back to the assumptions and financial mechanics that produced them.
AI-assisted workflows
AI helps organize research, structure inputs, and accelerate analysis while keeping users in control.
Damodaran-inspired methodology
The platform follows fundamental valuation ideas adapted into auditable software workflows.
Scenario analysis
Compare base, downside, and upside cases without rebuilding fragile spreadsheet versions.
Built for modern investment research
A structured workspace for investors, analysts, students, and founders working from fundamentals.
Methodology
Fundamental valuation principles, structured into software.
astrys.ai is built around fundamental intrinsic valuation principles, with a focus on FCFF valuation, cost of capital, country risk, bottom-up beta, synthetic credit ratings, R&D capitalization, and multi-scenario forecasting.
FCFF valuation
Country risk premiums
Bottom-up beta
Synthetic credit ratings
R&D capitalization
Multi-scenario forecasting
The methodology draws inspiration from the valuation framework developed by Aswath Damodaran and industry best practices and adapts it into structured, auditable software workflows.
Explore MethodologyFounder
Ian Verbeylen
Founder
astrys.ai was created to combine rigorous valuation thinking with modern software engineering. The goal is to help users move from scattered assumptions and fragile spreadsheets toward structured, explainable valuation workflows.
- Master's in Business & Law
- Background in valuation, financial modeling, and software engineering
- Building proprietary valuation infrastructure inspired by academic frameworks and best practices
- Building astrys.ai to combine valuation expertise with AI-powered financial analysis
Principles
Product beliefs that keep the platform grounded.
Transparency
Every assumption should be visible, editable, and understandable.
Assumptions First
The quality of a valuation depends on the quality of the underlying assumptions.
Explainability
Users should understand how outputs are produced, not just receive a final number.
Continuous Improvement
Models, data, and workflows should improve as new information becomes available.
astrys.ai
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