I was curious about how the creator economy actually works, not the influencer marketing pitch decks, but the actual structure.
- Who mentions who in their videos?
- Which brands keep showing up across the same creators?
So I built a pipeline that analyzes YouTube videos at scale, extracts every person mentioned and every brand sponsor, and builds a relationship graph from it. No manual data entry. Everything is extracted from what creators actually say and show.
Current data: 32K creators, 55K relationship edges, 2,700 brands. Started deep in fitness and gaming YouTube.
Things to try out:
- Search "Gymshark". See their sponsored creators, which categories they target, and which brands compete for the same roster
- Search "MrBeast". See his connection network
- Click a category tab on the homepage to filter both creators and brands
The hardest technical problem was entity resolution. The same person gets mentioned as "Jeff Nippard", "Jeff", "Nippard" across thousands of videos. Getting that right is what makes the graph useful.
Stack: FastAPI, Next.js, PostgreSQL, Fly.io. Gemini 2.0 Flash for structured extraction.
No signup, no paywall.
