About
Econosysmographe is built by a team with a simple conviction: risk intelligence should move beyond pattern recognition — toward measurable, auditable market structure.
The founder
Evangelos Papadopoulos — Founder
Evangelos is a senior technology and quantitative-architecture executive with over 30 years of experience delivering mission-critical business systems for financial institutions and large organisations — with a career built on bridging high-level business strategy and complex technological execution.
With Econosysmographe, he leads a deliberate shift away from black-box machine-learning models toward financial geometry: using Lorentzian geometry, manifold learning and causal mapping to identify structural market ruptures before they surface as systemic risk. The design principle is constant across the platform — deterministic computation, published methodology, and readings a validation team can re-run and verify.
His engineering background spans the full development lifecycle — architectural strategy (TOGAF), agile delivery, cloud infrastructure, distributed streaming systems — now applied to high-performance geometric modelling. The result is a conviction that runs through everything on this site: risk intelligence should be causal and auditable, not merely pattern-matched.
The team
Dr. Nicholas Georgiadis
Managing Partner & Director of Equity Research
Meher Selmi
Lead Data Scientist
Godwin Sweto
Senior Executive Business Advisor, MBA
The company
Econosysmographe is developed and operated by SmartGreenInvest Ltd, registered in England & Wales (Company No. 14636473), with the platform’s computation engine built on Trident-AI technology. SmartGreenInvest Ltd is not authorised or regulated by the Financial Conduct Authority. The methodology is published under the Universal Risk Framework and documented in five research papers available on SSRN — see Research.
How we use AI — stated plainly
In the readings: no AI. The platform’s measurements are deterministic geometric computations on public market data. No machine-learning model produces, adjusts or filters a reading. Identical inputs always yield identical results — that is the point.
Around the readings: AI, under human review. We use AI tools to assist with drafting written content, producing videos, and powering in-platform explanations. Every published analysis is authored and reviewed by the team; the interpretation and its limits are ours.
Meet us on this week’s market.
A 30-minute discovery session: a demonstration of the platform on current market data, and a conversation about where structural risk hurts in your process.