CLUSTER MOOD-MOVIES-RECOMMENDS · 27 ENTRIES · EARLIEST ENTRY 2025-07-18
Movie recommendation apps
This cluster consists of movie and TV recommendation apps that suggest titles based on preferences, mood, similar content, or user matching. Dated entries appear sporadically from June 2025 to July 2026, with small counts each month and no consistent upward trend. Track-it leads on traction with 3 stars, while the other dated members have 0 stars.
Entry timeline
ENTRY TIMELINE
Each bar is the month a member carries, which is a creation date where the source published one and a crawl date otherwise. Nothing in the index was found before 11 August 2026, and coverage broadened sharply on 14–15 August, so a bar from then on reports how much we found that month, not how much was built; an earlier bar reports how far back a member's own source dated it — not how long we have been watching.
Members by activity
Activity signals, not revenue.
Build origin · 3 ai-built · 3 hand-coded · 14 unlabelled
Operator · 13 hobby · 7 unlabelled
Two labels per entry, never collapsed into one: how it was built, and who stands behind it. Counted over the 20 listed below. Unlabelled means nothing has decided yet — not that the answer is small.
- 01Moviemaxx2★15 days—Chat-based movie recommender that suggests Bollywood films from a large catalog based on user preferences.
- 02nedflichs0★1 mo—hobbyStreaming recommendation app that suggests films and series based on the user's mood, available time, and accessibility needs.
- 03OTT-Intelligence-Platform0★todaylivehobbyWeb app that recommends movies and TV shows from psychological profiles and taste preferences.
- 04movie-recsys-fastapi-react0★22 days—hobbyMovie recommendation website where users rate films and receive personalized picks based on their ratings and popularity.
- 05AI-Projects0★14 days—ai-builthobbyApp that creates a personal wishlist of recommendations from trusted people, tracking who suggested each movie, restaurant, or other item.
- 06REEL-FINDER0★15 days—hobbyWeb app that lets users discover movies through natural-language search and personalized recommendations based on preferences and interactions.
- 07tonights-pick0★11 days—hand-codedMovie and TV show recommendation app that suggests titles based on user preferences.
- 08recsbot0★1 mo—hand-codedhobbySelf-hosted chat app that recommends movies and games based on user preferences and taste data from Steam and Jellyfin.
- 09CineFinder0★1 moliveWeb app that helps users discover movies based on preferences.
- 10movie-recommender0★1 moliveWeb app that recommends movies to users based on their preferences.
- 11kino-oracle0★1 mo—hobbyMovie recommendation app that learns taste from swipes and suggests a single film for the evening with a personalized reason.
- 12marquee0★1 mo—hobbyLocal-first film recommender that selects one movie for the night, explains its reasoning, and notes potential dislikes.
- 13movie-recommendation-system0★1 mo—Recommends movies to users based on their preferences and viewing history.
- 14cinematic-connection0★1 moliveai-builthobbyWeb app for matching users based on their movie preferences, suggesting matches and shared film interests.
- 15fr0★1 mo—hobbyWeb application that randomly picks a movie category and displays film suggestions for that category to help users decide what to watch.
- 16taste-explorer-unlocked7★1 yrabandoned—ai-builtApp that recommends movies, music, or other content to users based on their personal taste preferences.
- 17NeIzlesek0★2 mo—hand-codedhobbyMobile app that recommends movies and series based on user preferences and enables matching with others on shared taste.
- 18MovieMatch1★7 mostale—hobbyMobile app where users swipe on movies to find people with matching taste and receive personalized film recommendations based on shared preferences.
- 19Cue Entertainment0★6 moliveApp that recommends movies and TV shows based on user preferences and mood so viewers spend less time deciding what to watch.
- 20CineMatch0★11 mostale—hobbyWeb app that recommends movies to explore and rate based on genre and rating similarity to user preferences.
Ranked by traction, highest first, and paged 20 at a time — this is a window on the cluster, never the whole of it. Ties are broken by a stable id so a product cannot appear on two pages or fall between them. Browse every cluster.