Captum is an extensible library that provides general-purpose implementations for model interpretability in PyTorch. It aims to demystify complex machine learning models by offering several algorithms to analyze and understand model predictions. Captum includes a variety of methods such as feature ablation, integrated gradients, and others, which help researchers and developers to comprehend and improve their models.

Imandra offers a cloud-native automated reasoning system designed to bring rigor and transparency to the analysis and design of complex algorithms. With Imandra, users can convert input into mathematical logic and automate reasoning processes, ensuring safety, fairness, and compliance of algorithms. Imandra is especially suitable for high-stakes industries such as finance, where the reliability of algorithms is critical.