About DeepCausality

What is DeepCausality

DeepCausality is a dynamic-causality framework that enables fast, deterministic, context-aware causal reasoning over complex multi-stage causal models. The library adds only minimal overhead and runs in real time without specialized acceleration hardware.

It is used in dynamic control systems for the IoT industry, in monitoring systems for the cloud industry, and in dynamic market models in the financial industry. Start-ups looking to disrupt established categories also find the library a useful foundation.

See the documentation for the formal treatment, and check the blog for project updates.

Linux Foundation

DeepCausality is hosted as a sandbox project at the Linux Foundation for data and artificial intelligence. The Linux Foundation is the world’s leading home for collaboration on open-source software, hardware, standards, and data. Linux Foundation projects are critical to the world’s infrastructure, including Linux, Kubernetes, Node.js, ONAP, RISC-V, SPDX, and OpenChain. The Linux Foundation focuses on advancing best practices and addressing the needs of contributors, users, and solution providers to create sustainable models for open collaboration. More at linuxfoundation.org.

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