About Us

Born from Deep Industry Experience

About Our Company
Founded by former McKinsey and EY consultants with extensive commodity trading and AI development expertise. We’ve seen firsthand how the best trading firms operate and where technology can create sustainable competitive advantages.
The Gap We Identified

Trading firms excel at market analysis but struggle to integrate the supply chain intelligence that actually drives commodity price movements. Building in-house AI capabilities requires years and millions in investment.

Our Approach

We build custom AI systems that integrate seamlessly with your existing trading operations. Your traders keep doing what they do best while our AI agents handle the complex data synthesis and pattern recognition.

Shaun Nel

Former McKinsey & EY, University of the Witwatersrand (BSc Zoology)

Leadership

Meet our Founder

  • Systematic Trading Expertise

    20+ years developing systematic trading strategies and market intelligence systems.

  • Board-Level Industry Experience

    Board-level experience in mining and renewable energy.

  • Global Commodity Supply Chain Insight

    Deep understanding of global commodity supply chains from producer to consumer.

"The best trades happen when you see the supply disruption coming and position before the market realizes what's happening. Our AI gives traders that advantage at scale."

Our Technology Philosophy

We believe in AI that augments human expertise rather than replacing it. Our agents handle the data processing complexity while traders focus on strategic decision-making and relationship management.

Enterprise-Grade AI Architecture

Multi-Agent Intelligence

  • Specialized AI agents for different data domains
  • Continuous learning from market outcomes
  • Dynamic strategy adaptation based on changing conditions

Real-Time Data Integration

  • API connections to 200+ global data sources
  • Millisecond latency market data processing
  • Automated data quality validation and cleaning

Advanced Forecasting Models

  • Machine learning ensemble methods
  • Deep neural networks for pattern recognition
  • Bayesian inference for uncertainty quantification
  • Monte Carlo simulation for scenario analysis

Enterprise Security

  • End-to-end encryption for all data transmission
  • SOC 2 Type II compliant infrastructure
  • Multi-factor authentication and access controls
  • Regular security audits and penetration testing