Case Study: Paytm Lab accelerates feature delivery with Zencoder

How Zencoder streamlined workflows and accelerated development by automating repetitive tasks in a legacy code module

Paytm Lab was facing intense pressure from tight deadlines and a legacy code module that was burdened by manual, error-prone tasks. This outdated process was slowing down their feature delivery and escalating the time required for debugging. To address this challenge, they turned to Zencoder.

By integrating Zencoder's AI coding platform into IntelliJ, the team implemented context-aware code suggestions and a 'Generate' feature to streamline workflows and reduce repetitive tasks. This solution provided refactoring guidance for their legacy modules. The results were significant: feature delivery was accelerated, the workload on critical modules was reduced by half, and performance was boosted by 30%. Zencoder also minimized errors, which greatly reduced debugging time and instilled greater confidence in their releases.

Paytm

Zineng Yuan

Paytm Lab Developer