VibeMap
A TV and film discovery app that surfaces shows by themes, perspectives, and emotional texture rather than genres or streaming-platform rows.
Viewers burned out on generic streaming recommendations who want to find shows that match specific values or moods
- Theme-based discovery filters like 'feminist crime dramas,' 'anti-patriarchal comedies,' and 'subversive family sagas'
- Negative filters so users can skip gratuitous violence, reductive stereotypes, or trauma-as-plot devices
- Editorial moodboards from critics and writers, updated weekly around new releases and anniversaries
- Personal watchlist with rationale tagging so users remember why they saved a show
The Guardian's review of Disney+'s 'Furious' shows viewing choices increasingly hinge on values and perspective, yet Rotten Tomatoes and algorithmic home feeds flatten everything to a star score — leaving theme-conscious viewers to hunt through Reddit threads.
Strong streaming-fatigue signals — Limelight reports 51% of streamers can't find content and 54% of Gen Z trust social over platform algorithms; UserTesting confirms ~20% find it harder to find something to watch than a decade ago.51% of Streamers Can't Find Content: The Data | Limelight ↗Streaming Media Survey: Viewers Can't Find What To Watch ↗
Market is crowded with adjacent solutions: Moodvies, Moodies, MoodMuse, CineMood already target mood; Mubi ($1B valuation, 200k subscribers lost in PR storm) does values-based curation; Letterboxd and Reddit threads serve theme/values discovery for free.Moodvies, Movies For Your Mood ↗Mubi Hit Hard by PR Storm, but 2026 Looks Brighter - Variety ↗
Mubi proves people pay for curated film discovery ($77M ARR), but most mood apps are free and Reddit/social provide no-cost alternatives; willingness to pay for a third-party discovery layer on top of expensive streaming subscriptions is unproven.MUBI Revenue 2024: $77M ARR, $1B Valuation - LATKA ↗
Streaming fatigue is structural and unlikely to fade, but values/perspective tagging is subjective and culturally volatile (Mubi's 200k subscriber loss over a values stance shows the risk); algorithmic discovery will be increasingly commoditized by Netflix/Prime themselves.Mubi lost 200,000 subscribers in 2025 due to Sequoia controversy ↗
Core build is feasible via TMDb + LLMs for theme/perspective tagging, but creating reliable, non-superficial 'values and emotional texture' metadata at scale is hard and risks being out-built by the streamers' own recommendation teams (Netflix actively investing here).Netflix Uses Generative AI and Recommendation Engine Technology to Simplify Content Discovery ↗