Sitefire (YC W26) is a platform helping brands improve visibility in AI-powered search results, taking a data-driven app
We’ve been working together for years and have backgrounds in RL/optimization at Stanford and software engineering. We came to this idea after speaking with marketing teams who were seeing declining traffic due to Google’s AI Overviews and didn’t know what to do.
This space can feel esoteric. Many case studies, few actual studies. Constant battle against myths (e.g. you need a llms.txt vs. you don't need a llms.txt) and "GEO hacks". We try to be more data-driven. And we try to be more bold and build a system that not only monitors, but actually improves traffic from AI search.
While Google performs a single search, AI search engines expand the user prompt into 3-10 fan-out queries. The sourced pages are ranked using a classified algorithm similar to Reciprocal Rank Fusion (RFF). Finally, the LLMs skim the pages and decide what snippets to cite. Our goal is making sure brands have the right content that makes it through this funnel.
Here is how sitefire works:
- The user defines a set of prompts they want to monitor. These are synthetic prompts - we generate them based on SEO keywords and their monthly search volume.
- We submit these prompts to ChatGPT, Gemini, Google AI Mode, etc. on a daily basis and capture the answers. We extract fan-ou