Case Study: Razorpay achieves 10x faster AI model development with DataRobot

How one of India’s largest fintech players builds AI models 10x faster

Razorpay, one of India’s largest fintech firms, needed an AI platform that non‑data scientists could adopt quickly while providing transparency, bias mitigation and seamless integration into its AWS‑based stack. With a small data science team and high‑stakes use cases across payments, risk and fraud in a regulated environment, Razorpay was looking to scale experimentation and empower engineers and business users without increasing headcount.

Razorpay implemented DataRobot (via the AWS marketplace) to give teams self‑service model building, monitoring, and fairness controls. Using DataRobot, Razorpay cut model development from roughly five days to under four hours (about a 10x speedup), built an AI fraud solution in a 12‑hour “war room,” deployed it the next day to block malicious orders, and now relies on DataRobot’s drift detection and bias‑mitigation features to keep models safe in production.

Razorpay

Pranjal Yadav

Head of AI/ML