Co Founder & CEO, Wealth AI

Building market intelligence.

Founder, quantitative researcher, and engineer. At Wealth AI, I build the research layer between raw market data and decisions investors can audit.

See what I am building Get in touch
Quantitative researcher Building Wealth AI Based in Frankfurt
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Experience across
  • Deka Investment
  • DekaBank
  • J.P. Morgan Chase
Portrait of Jayden Bruck
Jayden Bruck Frankfurt, Germany
About

Institutional rigor.
Builder execution.

I work where artificial intelligence, financial markets, and systematic trading meet. Since 2022 I have traded quantitatively while studying how institutional markets are researched, tested, and executed.

At Deka's Quantitative Asset Management branch I joined the Alternative Strategies team on the Frankfurt trading floor, studying systematic alpha, derivatives, and execution in detail. That standard shapes how I build.

Today I am Co Founder & CEO of Wealth AI. I lead the AI research layer between raw market data and better financial decisions, with code close to every claim.

  • Trading since2022
  • Based inFrankfurt
  • LanguagesDE / EN / ES / PT
Currently building

Wealth AI

Wealth AI is a financial intelligence system for market research at scale. It structures price, volatility, liquidity, momentum, regime shifts, and cross asset relationships into evidence investors can test.

  1. 01

    Market data at scale

    Pipelines collect, normalize, and version financial data across assets and timeframes, creating the material every model depends on.

  2. 02

    An AI research engine

    Models, statistical validation, backtesting, and GPU workflows are coordinated by research agents inside one reproducible engine.

  3. 03

    Tested insight

    No signal matters until it survives leakage checks, baselines, and out of sample review.

Structured for EU compliance under MiCAR, with Austrian counsel at CERHA HEMPEL.

Inside the research

A research system,
not a trading bot.

An applied platform for multi asset market prediction. Data engineering, machine learning, validation, and autonomous agents work as one research loop.

Coverage
  • Crypto
  • Equities
  • ETFs
  • Forex
  • Broader liquid markets
Exploring
  • multi timeframe transfer
  • asset specific meta gating
  • abstention and calibrated confidence
  • prospective evidence rails
Research graph Evidence first
  1. 01 Data
  2. 02 Features
  3. 03 Models
  4. 04 Validation

Data engineering

Point in time pipelines keep the future out of the past.

  • raw ingestion
  • point in time features
  • multi timeframe labels
  • event bars
  • evidence tracking

Models

Architectures are tested on whether they improve decisions over multi day horizons.

  • foundation models
  • time series models
  • gradient boosting / XGBoost / LightGBM
  • transformers
  • LSTM / GRU
  • ensemble methods
  • LLM news interpretation
  • custom predictive nets

Validation

Every claim earns its place through controlled tests.

  • frozen datasets
  • leakage controls
  • purged validation
  • baselines and null models
  • multiplicity controls

Orchestration

Autonomous research runs reproducibly at cloud scale.

  • reviewer agents
  • cost aware execution
  • reproducible packages
  • claim bounded dashboards

The goal is a cross asset intelligence layer that reads market state, makes disciplined directional calls, and knows when not to act.

What I lead

From research direction to regulatory work.

Strategy & Leadership

Company direction, product judgment, and technical priorities. Clear decisions under uncertainty.

AI & Quant Research

Turning raw market data into tested intelligence with modern time series modeling and statistical validation.

Research Infrastructure

Data pipelines, model evaluation, backtesting frameworks, GPU workflows, and validation harnesses.

Product & Engineering

Architecting the systems that turn research outputs into product, with researchers, agents, and cloud workflows aligned.

Go to Market & Brand

Positioning, content, and customer acquisition from zero to a focused audience.

Regulatory & Legal

MiCAR positioning with experienced counsel, keeping the product compliant and capable.

What I believe
  1. 01

    Markets are systems. Systems can be modeled.

  2. 02

    The best research is built in code, then tested against the past without leaking the future.

  3. 03

    Clarity beats noise. The work should reveal one honest view.

  4. 04

    Move fast, think from first principles, build systems that compound.

  5. 05

    Lead by clear thinking and proximity to the work. Hierarchy is not the point.

The path

A line from early research to the trading floor.

  1. 2022

    Began trading systematically

    Quantitative research and crypto trading in code.

  2. 2024

    DekaBank Deutsche Girozentrale

    Internship in Frankfurt with exposure to a major institutional asset manager.

  3. Dec 2025

    Founded Wealth AI Co Founder & CEO

    Started the AI research layer between market data and better decisions. Wealth AI Software GmbH, Vienna.

  4. Jan 2026

    Deka Investment, Quantitative Asset Management

    Youngest intern on the Frankfurt trading floor, embedded with the Alternative Strategies team.

  5. Apr 2026

    J.P. Morgan Chase

    Internship in Frankfurt across Capital Markets and Equity Research.

  6. Now

    Building Wealth AI full time

    Scaling the research engine while the product layer takes shape behind it.

Where I am going

A world where more people can read markets with institutional discipline. Raw data becomes a decision process they can inspect, challenge, and trust.

Wealth AI is the first step.

Get in touch

Let's talk.

Building serious financial technology, investing in AI infrastructure, or comparing notes on markets? I would like to hear from you.

jayden.bruck@wealthai.trade
Jayden Bruck signature
Jayden R. Bruck / Founder & CEO