ABOUT

THE SYSTEM AND ITS BUILDER

CORVUS (Composite Operational Risk & Vulnerability Understanding System) is an automated geopolitical risk intelligence platform built on the conviction that mechanism-based analysis will always outperform sentiment scoring.

THE NAME

CORVUS

The corvid family (crows, ravens, magpies) are among the most intelligent animals on Earth. They are known for pattern recognition across complex environments, tool use and manufacturing, causal reasoning, and the ability to plan for future events.

These are the same capabilities CORVUS brings to geopolitical analysis: detecting patterns across noisy data environments, using mathematical tools to decompose complex systems, reasoning about causal chains, and forecasting future states through probabilistic modeling.

FOUNDER

DORUK ÜNAL

SOLE FOUNDER & DEVELOPER

CORVUS is a solo-built system. Every algorithm, every collector, every frontend component, every API endpoint was designed, implemented, and tested by one person. This matters because it demonstrates:

DOMAIN EXPERTISE

You cannot build a 7-algorithm interconnected geopolitical risk engine by stitching together tutorials.

ARCHITECTURAL DEPTH

54-table schema, 10-phase pipeline, 102 API endpoints, all coherent and integrated.

ANALYTICAL INNOVATION

Irreversibility scoring, contradiction detection with historical precedents, bifurcated forecasting, multi-bloc information analysis.

EXECUTION VELOCITY

From concept to 102 API endpoints, 54 database tables, and a 10-phase pipeline. Shipped and operational.

MISSION

BUILD THE ANALYTICAL INFRASTRUCTURE THAT GEOPOLITICAL RISK ANALYSIS DESERVES

The geopolitical risk analytics market is projected to reach $15.26 billion by 2035 at a 17.42% CAGR. Yet the tools available to analysts, from defense ministries to hedge funds, remain largely anchored to sentiment scoring and expert-in-the-loop workflows.

CORVUS exists because risk analysis should be mechanism-based, not opinion-based. Because contradictions between signals matter more than any single score. Because the question “Is this still fixable?” matters more than “How bad is it?” And because mathematical rigor and analytical depth should not require a $1M+ contract and a team of analysts.

ANALYTICAL PHILOSOPHY

PRINCIPLES

MECHANISM OVER SENTIMENT

If you cannot explain the causal chain from data to conclusion, the conclusion is noise. Every CORVUS output traces back through a defined analytical pathway.

MATH OVER VIBES

Eigenvalue decomposition. Bayesian inference. Percolation theory. Information entropy. The tools of physics and mathematics applied to geopolitical systems.

CONTRADICTION IS SIGNAL

When your own algorithms disagree, that disagreement itself is intelligence. The most dangerous situations hide in the gaps between signals.

REVERSIBILITY MATTERS

A high risk score with recovery pathways is fundamentally different from a moderate score with no exits. The distinction saves lives.

TRANSPARENCY OF METHOD

Every score decomposes into its inputs. Every AI analysis logs its routing decision. Every contradiction cites its historical precedent.

HONEST UNCERTAINTY

When the data supports two genuinely different futures, CORVUS maps both branches instead of producing an analytically dishonest average.

LIMITATIONS

WHAT WE ARE STILL BUILDING

Analytical honesty requires acknowledging limitations:

//No systematic backtesting yet. Historical calibration is algorithm-specific, not system-wide
//Data gaps in Sub-Saharan Africa and Central Asia where source coverage is thinner
//AI reasoning layer depends on LLM analytical quality. Framework routing mitigates but does not eliminate LLM limitations
//Architecture designed for team-scale development and organizational deployment
//Financial market overlay is correlation-based, not yet causal

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