Resources
Documentation, tutorials, and guides for building with Nimbus BCI technology.
Python SDK Documentation
Complete guide to nimbus-bci: installation, API reference, examples, and best practices for sklearn-compatible BCI inference.
Julia SDK Documentation
NimbusSDK.jl reference: reactive Bayesian inference with sub-20ms latency for high-performance BCI applications.
Nimbus Studio Guide
Learn how to use the visual pipeline builder, export code, and work with various EEG hardware devices.
Getting Started with Python SDK
Quick start tutorial: Install nimbus-bci, train your first BCI model, and run real-time inference in minutes.
Active Inference & Probabilistic AI
Understand the theory behind Nimbus: Active Inference, Bayesian inference, and uncertainty quantification in BCI.
Book a Demo
Schedule a personalized demo with our team to see Nimbus in action and discuss your specific BCI use case.
Need Help?
Our team is here to help you get started with Nimbus BCI. Whether you're a researcher, developer, or company exploring BCI technology, we're happy to assist.