video1.0<iframe src="https://www.loom.com/embed/1888d82059ee40a78d2d6a8ed47e0805" frameborder="0" width="1728" height="1296" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>12961728Loomhttps://www.loom.com12961728https://cdn.loom.com/sessions/thumbnails/1888d82059ee40a78d2d6a8ed47e0805-cd7863ef7fca4c7d.gif301.057In this Loom, I walk you through AnishSignal, a system I built to automate data collection and pattern extraction so you do not have to manually sift through massive noisy datasets. It is a multi agent pipeline with data ingestion to final analysis, deployed with a lightweight Streamlit UI on Streamlit Cloud. Behind the scenes, the backbone is powered by LangGraph, routing tasks between agents using Ollama for processing, organized into four layers and 15 files to isolate ingestion from extraction. In a live demo, I show login, run pipeline for an ESP32 topic, and the generated content like gap summary, evidence track, risk flags, and graphs, with chat export enabled.