Use Cases

Optimize simple trading apps like finos-traderX that lets you develop, backtest, and deploy strategies so firms can accelerate time-to-market, reduce engineering overhead, and integrate seamlessly with real-time data and broker APIs.

Speed up backtesting workflow runtimes by up to 40x on CPU.

Accelerate optimization tasks in finance models using the SLSQP algorithm by 15.6x times faster runtime.

Achieve runtime acceleration in high-frequency trading with CUDA-tuned fundamentals.

Translate COBOL to languages like C, C++, CUDA, Golang, Java, Julia, Matlab, Python, or R to reduce tech debt.

Modernize COBOL-based machine learning workflows by reducing training time from minutes to seconds. Learn how optimizing legacy COBOL code improved runtime performance by 5x, cut CPU usage costs, and enabled faster model iteration—critical for financial services relying on fraud detection, credit scoring, or risk modeling.

Improve performance in budgeting software through core-level C++ optimizations.

Leverage a smart GC library to improve runtime in high-throughput finance systems.

Accelerate calculations for stock indicators with optimized .NET-based tools.