Building Tomorrow's Financial Intelligence

We're not just another fintech company. Since 2019, we've been quietly revolutionizing how financial institutions process streaming data through machine learning—one algorithm at a time.

What Drives Us Forward

Every line of code we write, every model we train, stems from three fundamental beliefs about the future of financial technology.

Real-Time Intelligence

Traditional financial systems react to market changes. We believe in predicting them. Our streaming algorithms process over 50,000 data points per second, turning market noise into actionable insights.

When a major bank reduced their risk exposure by 23% using our predictive models during the 2024 volatility spike, we knew we were onto something significant.

Research-First Approach

We spend 40% of our time researching because markets evolve faster than most people realize. Our team includes former quantitative researchers from three different continents, each bringing unique perspectives on market behavior.

This isn't about following trends—it's about understanding the mathematical patterns that drive global financial markets.

Partnership Over Products

We don't sell software; we build relationships. Every client gets a dedicated research team because your trading challenges are unique. Generic solutions don't work in algorithmic trading.

Our longest partnership started in 2020 with a small hedge fund. They're now managing 8x their original capital using systems we developed together.

How We Actually Work

Forget the typical tech company rhetoric. Our Ipoh office might seem unconventional for a fintech startup, but that's exactly why it works. Being outside Kuala Lumpur means we focus on building rather than networking.

Our team starts each day analyzing overnight market movements from New York and London. By 10 AM, we're already adjusting algorithms based on fresh data patterns. This isn't a 9-to-5 business—markets don't sleep, so neither do our systems.

Direct access to global market feeds from our Perak headquarters
Cross-functional teams where researchers and developers work side by side
Monthly algorithm reviews with external quantitative analysts
Continuous learning budget for emerging financial technologies

"The best trading algorithms come from understanding both mathematics and human psychology. Markets are just collective human decisions expressed in data."

— Priya Chandran, Lead Quantitative Researcher