Wolk

Like many financial processes that evolve over time, our client's settlement system had grown increasingly complex and brittle. What began as a simple script had morphed into an unwieldy process requiring significant manual oversight and intervention. In order to grow their virtual power plant, these processes needed to be automated.

Our solution implemented a three-layer architecture that cleanly separated data loading, business logic, and output generation. Using Python with Polars for efficient processing and Patito for dynamic column referencing, we built a platform-independent system that elegantly handled timezone differences, varying timestamp granularities, and inconsistent units of measurement.

We rebuilt the entire process from the ground up using modern software engineering principles rather than applying quick fixes. This comprehensive approach eliminated intermediate manual steps while implementing robust validation and error handling, creating a fully automated pipeline that dramatically improved reliability.

Our modular architecture was designed with the future in mind, readily supporting API integrations, automated testing pipelines, database connections, and workflow orchestration—positioning our client for continued growth and innovation.

Werk

We transformed a manual, error-prone settlement system into a robust automated solution focused on accuracy, reliability, and scalability—essential qualities for financial operations.

Multiple data sources with inconsistent formats.

Excessive manual intervention undermining reliability.

Legacy systems ill-equipped for future requirements.