PHDiego Mendoza
Elite
Cinemetrica is a movie and TV show discovery tool built by an indie creator who analyzed 2,000+ films and shows across 38 distinct dimensions to solve the classic "what to watch" problem — specifically that frustrating experience of endlessly scrolling while your dinner goes cold.
How It Works
Rather than relying on genres or basic keyword matching, Cinemetrica maps titles across multi-layered attributes like plot complexity, humor register, and pacing. The idea is that you tell it a few titles you loved, and it uses those 38-dimensional profiles to surface something that truly matches your taste — not just surface-level similarity.
What Makes It Different
Most recommendation engines (Netflix, IMDb, etc.) match on genre tags, popularity, or collaborative filtering ("people who watched X also watched Y"). Cinemetrica's approach is closer in spirit to enterprise tools like Cineverse's cineSearch, which also aims to understand films "intrinsically" rather than from metadata alone — but Cinemetrica appears to be a solo indie project, not a corporate product, which gives it a scrappier, more passionate feel.
Key Highlights
- 2,000+ titles analyzed manually or semi-automatically across 38 dimensions
- Dimensions include nuanced qualities like pacing, humor register, and plot complexity — not just genre
- Designed for a casual, couch-viewing use case (find something before the pasta gets cold)
- Built and shared by an individual creator, likely as a passion/side project
Quick Take
It's a promising concept — the 38-dimension framework is genuinely differentiated from mainstream recommenders. The key question is whether the dimension scoring is subjective/manual (which limits scalability) or AI-assisted. It'd be worth testing it with a few niche favorites to see how well the multi-dimensional matching holds up against something like a Letterboxd-style taste profile.
Find Your Next Favorite Film here: