ReAgent is an end-to-end reinforcement learning platform built with Python and PyTorch. It provides workflows for training popular deep RL algorithms including DQN, Double DQN, Dueling DQN, C51, and QR-DQN variants. The platform handles the full ML lifecycle from data preprocessing and feature transformation through distributed training and counterfactual policy evaluation, to optimized TorchScript model serving.