Recommendations based on TV metadata
Viewer watched on TV → recommend in streaming. Cross-platform personalization.
The Problem
Recommendation systems don't know what viewer watches on TV. Personalization incomplete.
How it works
Cross-platform viewing data
ML based on full metadata
Content IDs for deduplication
API for integration
Benefits
Cross-platform
TV + streaming = complete picture
Retention
Accurate recommendations retain
Discovery
Viewers discover new content
ML ready
Data ready for your models
More for streaming
Schedules for 4308 channels. Completeness, accuracy, real-time updates.
Genres, cast, studios, ratings, posters, stills.
All platforms speak one language. Recommendations work, reruns don't duplicate, TV and VOD are linked.
Restricted content markers. Shared risk and responsibility.
Every program start within ±3 sec accuracy. Catch-up opens right from the first frame.
Metadata + images already collected. Rights holders upload — you receive.
OpenAPI 3.0, JSON, clear endpoints.
Logos, descriptions, contacts, website, social media, broadcast language.
Channel broadcast geography. Which channel is available in which region.
Sport type, championship, teams, persons + posters.
100% episodes filled. Better viewer experience, catch-up without duplicates, accurate recommendations.
Ad breaks and promos marked. For skip features.
Mapping linear TV and VOD catalog. Unified content space for recommendations.
Rights holders upload data themselves. Single format, no manual work.
Ready to connect AI Recommendations?
Tell us about your needs — we'll find the optimal solution.