Modernizing payment reconciliation at a top-5 global processor

The platform, written in Delphi, managed exception ticketing, executed funds movement, and carried seven-year data retention obligations. A single drive failure or bad reboot created a real probability the system would never come back up, and manual reconciliation at that volume was not an option.

PraxentDecode℠ often surfaces architectural boundaries the original team did not know existed. In this engagement what the organization treated as one system was actually three applications running as one: downloads, daily reconciliation, and bank reconciliation.

A reverse-engineering agent reads the source code, builds an internal model of how the system behaves, raises the questions only humans can answer, and folds those answers back into traceable specs.

Rules like this live inside stored procedures and calculation methods, often
hard-coded hundreds of lines deep. They are the kind of detail a rebuild misses unless the original logic is recovered first.

Before LLMs, this kind of recovery relied on people, and the error rate was significantly higher than 5%. The structured, validated, agentic approach is faster and more accurate than what a human team typically produced.