About

A free map of where to build presence for AI search.

AI assistants answer from what they can read and who they can match you to. Most of that comes from a short list of public profiles, directories and data sources. This site ranks them so you know where an hour goes furthest.

Every score comes from the open awesome-geo repo. A script checks each platform's robots.txt, indexability and authority every Monday. If a number looks wrong, open an issue.

Facts

Platforms: 157 in 9 categories
Repos: 65 in 8 categories
Crawler checks: weekly, Monday 06:00 UTC
Data license: CC0-1.0
Maintainer: Dmitry (Dee) Kargaev

Research

Awesome GEO is built and maintained by Dmitry (Dee) Kargaev, a design engineer who studies how AI search engines choose and cite sources. He has published two papers on generative engine optimization.

The SEO-to-GEO Gap: Quantifying Ranking Factor Divergence Between Traditional and Generative Search Which ranking factors carry over from search to AI answers, and which do not. SSRN, 2026. DOI 10.2139/ssrn.6476021 SEEN: A Four-Layer Framework for Generative Engine Optimization A four-layer framework: Structure, Evidence, Entity, Notability. SSRN, 2026. DOI 10.2139/ssrn.6815500 Get SEEN The SEEN framework as an article and a checklist

Cite

The data is CC0, so no credit is required. If you cite it: Kargaev, D. (2026). Awesome GEO. https://geo.deeflect.com

Contact

Suggest a platform or repo Pull request or issue on GitHub Dmitry (Dee) Kargaev deeflect.com