DedAI is an independent software publisher whose work is distributed through its GitHub presence at github.com/HawkSP, where it maintains a small but focused catalog centered on a single specialized product. The publisher's flagship and currently sole package, DedAI Bridge, addresses a niche at the intersection of neurotechnology and software integration: it connects an EEG headset to the DedAI environment by streaming brain signals over a local WebSocket connection, using the open-source BrainFlow framework as its acquisition layer. BrainFlow is widely used in the biosignal community because it abstracts away the proprietary protocols of different headset manufacturers, which means DedAI Bridge can serve users working with a variety of consumer and research-grade EEG devices without requiring device-specific drivers. The product falls into the software category of hardware integration middleware and developer tooling, and its typical use cases include brain-computer interface prototyping, neurofeedback experiments, academic research on cognitive states, and hobbyist projects that need real-time neural data delivered to another application. By transmitting data over a local WebSocket rather than through files or shared memory, DedAI Bridge makes the signal stream accessible to any client capable of speaking standard web protocols, which suits workflows involving data visualization, machine learning pipelines, or interactive applications that react to live brain activity. The local-only design also keeps sensitive physiological data on the user's own machine, a consideration relevant to privacy-conscious research and personal experimentation. As a one-package publisher, DedAI represents the common pattern of a focused open-source effort built around solving a single integration problem well, offering the neurotechnology community a lightweight bridge between affordable EEG hardware and custom software built on top of it.

DedAI Bridge

Connects an EEG headset to DedAI, streaming brain signals over a local WebSocket via BrainFlow.

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