NeuroAIHub/BrainPilot

What it solves

BrainPilot is an AI research workspace designed to automate and structure the discovery process in brain science. It helps researchers manage the entire scientific lifecycle—from literature review and hypothesis refinement to experiment design, data analysis, and auditing scientific claims—reducing the burden of evidence-heavy and cross-disciplinary tasks while keeping the human researcher in control.

How it works

The system employs a multi-agent architecture centered around a Principal Investigator (PI) Agent. The PI coordinates a team of specialist agents, including a librarian, experimentalist, engineer, writer, and auditor. To ensure scientific reliability, an Auditor Agent specifically reviews evidence chains and citations to mitigate hallucination risks. The entire research process is recorded as a "Graph of Trace" (GoT), making every decision, action, and piece of evidence inspectable and traceable.

Who it’s for

It is built for brain science researchers who need an agentic system to help them navigate complex neuroscience datasets, review vast amounts of literature, and execute structured analysis workflows.

Highlights

• Specialized Multi-Agent Team: Uses a PI agent to coordinate specialists (librarian, experimentalist, engineer, writer, auditor).
• Scientific Auditing: Includes a dedicated Auditor Agent to verify claims and evidence chains.
• Traceable Workflows: Implements a Graph of Trace (GoT) to make the research process transparent and inspectable.
• Extensible Knowledge Base: Features a built-in library of 72 validated domain skills across 21 categories (e.g., EEG, fMRI, cellular neuroscience).
• Tool Integration: Connects to MCP tools, paper databases, and code execution environments.