Atlas Signal

What it is

Atlas Signal is a research paper library app designed for opportunity hunters, people who track emerging trends across science and technology to spot where the next opportunities are forming.

It presents academic research papers as a signal feed, styled like a newsletter or intelligence brief rather than a dry academic database. Each paper is scored and filtered so you can quickly judge what deserves your attention.

Key concepts

Signal scoring. Every paper gets a score from 0–100 indicating how relevant or impactful it might be:

Collections. Papers are organised by domain: Energy & Materials, Health & Bio, AI & Compute, Human Interface, Workplace & Cognition. Each collection works like a folder you can filter by.

Brief view. Each paper has a structured brief with an abstract summary, top application areas with sub-scores, and key takeaways, distilled so you don't need to read the full paper to understand its relevance.

Application threads. Papers are mapped to real-world industries and use cases (e.g. "Grid transmission 96 · MRI imaging 91") so the bridge from research to opportunity is explicit.

Who it's for

I built this for myself. Staying current across multiple domains of AI without reading hundreds of papers is a real problem I had, and the usual workaround of skimming abstracts and conclusions felt like it was losing too much along the way. Atlas Signal is my attempt at something better: get a sharp enough overview to know if a paper is worth your time, then go deep when it is.

This version is focused on CHI research papers in Explainability AI (XAI) and human-computer interaction. It's become a personal reading tracker for the work I'm doing on AI transparency and interpretability, which is where most of my thinking lives right now.

I could see it being useful beyond just me though. Researchers who want to ground their work in current literature, or strategists who need to sense where a field is moving before it moves, would probably find a tool like this useful too.