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What is Nimbus?

Nimbus is a dedicated environment tailored for research in brain-computer interfaces (BCI), concentrating on the creation, implementation, and evaluation of electroencephalography (EEG) workflows. It enables researchers and neuroengineering professionals to visually assemble processing sequences, leverage public datasets, upload personal data, and evaluate different model configurations, while also allowing users to export the entire workflow as Python code. This platform includes essential components for data preprocessing and machine learning, along with features for simulation, playback, model evaluation, and support for live EEG devices. Through Nimbus Studio, users benefit from a web-based visual builder as well as desktop applications compatible with both macOS and Windows, which support offline or local workflows. Moreover, its API allows for the execution of pipelines from external platforms, while the Nimbus MCP connects suitable AI coding clients with tools for searching datasets, developing pipelines, and conducting experiments. Users can start with a free tier for initial prototyping, while those who opt for paid subscriptions can enjoy enhanced features like greater run capacities, private data management, GPU computing capabilities, and access to live hardware functions. As Nimbus continues to evolve, its primary objective is to improve research efficiency and broaden accessibility within the BCI sector, making it an invaluable resource for both newcomers and seasoned researchers alike.

What is MLBox?

MLBox is a sophisticated Python library tailored for Automated Machine Learning, providing a multitude of features such as swift data ingestion, effective distributed preprocessing, thorough data cleansing, strong feature selection, and precise leak detection. It stands out with its capability for hyper-parameter optimization in complex, high-dimensional environments and incorporates state-of-the-art predictive models for both classification and regression, including techniques like Deep Learning, Stacking, and LightGBM, along with tools for interpreting model predictions. The main MLBox package is organized into three distinct sub-packages: preprocessing, optimization, and prediction, each designed to fulfill specific functions: the preprocessing module is dedicated to data ingestion and preparation, the optimization module experiments with and refines various learners, and the prediction module is responsible for making predictions on test datasets. This structured approach guarantees a smooth workflow for machine learning professionals, enhancing their productivity. In essence, MLBox streamlines the machine learning journey, rendering it both user-friendly and efficient for those seeking to leverage its capabilities.

Media

Media

Integrations Supported

Python
Claude Code
Claude Desktop
Codex CLI
Cursor
Julia
MATLAB
Model Context Protocol (MCP)

Integrations Supported

Python
GitHub

API Availability

Has API

API Availability

Pricing Information

$29/month
Nimbus Studio offers a free tier with 20 pipeline runs per month on public datasets, CPU compute, simulation and playback, Python export, and the AI assistant. Pro is $29 USD per month and adds unlimited runs, custom data uploads, cloud GPU compute, and live EEG deployment. Enterprise pricing is custom. Academic researchers may be eligible for extended free access.
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac
On-Prem

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Nimbus BCI

Date Founded

2025

Company Location

United States

Company Website

nimbusbci.com

Company Facts

Organization Name

Axel ARONIO DE ROMBLAY

Date Founded

2017

Company Website

mlbox.readthedocs.io/en/latest/

Categories and Features

Data Analysis

Not specified

Machine Learning

Not specified

Categories and Features

Machine Learning

Not specified

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