Institutionalizing AI-First SDLC to Improve Delivery Velocity and Operational Resilience for a Leading Payment Processor

A leading U.S.-based payment processor had been building and extending core transaction systems over decades. Critical payment logic lived in large, legacy codebases with limited documentation, and institutional knowledge was concentrated among a small group of experienced engineers. Onboarding new developers took up to six months, limiting the pace of delivery.

Client Challenges and Requirements

• Delivery velocity constrained by legacy complexity — decades of accumulated payment logic and limited documentation slowed development.
• High onboarding time created systemic knowledge risk — new engineers required up to six months to become productive.
• Modernization pressure without tolerance for instability — 99.99% availability and sub-100ms authorization latency could not be compromised.
• Manual, time-intensive data transformation — BigQuery-to-DBT migrations required significant manual effort.

Bitwise Solution

• Applied GitHub Copilot across the entire SDLC — development, testing, code review, documentation, and data transformation workflows.
• Used AI-assisted code understanding and documentation to surface logic embedded in large, legacy payment systems.
• Institutionalized an AI-first delivery model as standard across engineering teams with defined best practices and training.