Code Willing, Inc. has announced its advanced CWIQ platform, designed to empower hedge funds by streamlining data analysis workflows for model development, simulation, and backtesting. This innovative platform allows research teams to focus on data science, feature engineering, and alpha generation while optimizing elastic compute resources and data usage, driving competitive returns.
At the heart of this platform is CWIQ FS, a patented file system offering enterprise-level HPC scalability, simplified storage orchestration, and optimized performance, ideal for systematic trading and data science applications. By managing vast datasets across hybrid multi-cloud environments, CWIQ FS provides real-time metadata updates and integrates with object stores like S3, ensuring consistent and up-to-date views of firm data across locations.
Recognizing that inefficient trading simulation and backtesting results in unnecessarily high compute bills, Code Willing created the CWIQ Bench; the first self-service cloud compute system tailored to capital markets participants. It provides cost regulation and per-user budgeting, allowing quants to find, compare, and select the best compute resources—whether vCPUs, storage, or GPUs—ensuring efficiency across every workload.
Also Read: Airbyte Boosts Databricks Integration for Easier Data Consolidation
Rob Martinez, CRO of Code Willing, emphasized the platform’s unique ability to offer 100% budget visibility. “We designed the CWIQ Suite to avoid the complexity of unpredictable billing models while still offering cutting-edge performance. With per-user cost controls, our solution enables teams to forecast usage, eliminating end-of-month surprises and giving firms full control over cloud spending down to the penny.”
Paul White, CEO of Quantbot Technologies, had this to say about the platform: “We’ve been leveraging Code Willing for a few years now, and it’s really improved our data and research efficiency globally, but, more importantly, it’s significantly reduced our data discovery, trialing and onboarding costs. By leveraging the Code Willing platform, we’ve been able to repurpose our data team to focus more on data science and signals. We are now trialing about 150 datasets a year, which is a massive improvement for us.”
Source: PRNewswire