NeuroForge
One AI OS, six specialized agents for every workflow
10 followers
One AI OS, six specialized agents for every workflow
10 followers
NeuroForge AI is a multi-agent AI OS for real engineering & knowledge work. Six agents: Engineer AI (LangGraph Planner→Coder→Tester→Debugger), Research AI, Education AI, Automation AI, Conversational AI, plus an Admin/RAG Studio with org-level knowledge isolation (ChromaDB + Gemini embeddings). Built with FastAPI, LangChain, LangGraph, MongoDB, Groq, Docker. One unified OS instead of five separate tools. Built solo — would love feedback on agent orchestration & RAG design!
How does the org-level knowledge isolation actually hold up when multiple agents pull from overlapping documents at the same time, especially with the ChromaDB + Gemini embedding setup under load?
how does the agent orchestration actually work in practice when an engineer task needs input from the research agent mid-run, do they hand off context cleanly or does it get messy?
Shipping six coordinated agents as a solo build is genuinely impressive, and packaging them as one OS rather than scattered tools is a smart move. Curious how you're handling context handoffs between the Engineer and Research agents without losing state mid-task.