Recommendations that work
Personalization based on EPG Service metadata. More engagement.
Service scope and specifications
- Name
- AI Recommendations
- Purpose
- Personalized content recommendations based on EPG metadata.
- Scope
- Recommendation models; integration with the client catalog and EPG.
- Target audience
- Pay TV, IPTV and OTT operators.
- Technical specs
- REST API; ML models on metadata.
- Pricing
- Coming soon.
- Delivery
- SaaS / API access under a services agreement.
The Problem
Recommendations don't work without quality metadata and content links.
How it works
ML models based on full metadata
Content IDs for content links
Viewer personalization
API for integration
Benefits
Engagement
Viewers find interesting content
Retention
Lower churn
Data
Based on real metadata
API
Easy integration
More for operators
Schedules for 4K 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.
Every program start within ±3 sec accuracy. Catch-up opens right from the first frame.
EPG metadata translation for your audience's language. Works in your existing XMLTV/JSON integration. Languages: kz, en, more coming.
Content compliance with legislation. 6 risk categories, registry monitoring, age rating. Shared responsibility.
Channel broadcast geography. Which channel is available in which region.
Logos, descriptions, contacts, website, social media, broadcast language.
Sport type, championship, teams, persons + posters.
Stylized posters for sports broadcasts: team logos, tournament emblems, athlete portraits.
OpenAPI 3.0, JSON, clear endpoints.
Full schedule by actual broadcast, not planned.
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.
Frequently asked questions
What is AI Recommendations and what is it for?
Personalized content recommendations based on EPG metadata.
What does AI Recommendations include?
Recommendation models; integration with the client catalog and EPG.
In what formats is the data delivered?
REST API; ML models on metadata.
How to connect AI Recommendations?
SaaS / API access under a services agreement.
How much does AI Recommendations cost?
Coming soon.
Ready to connect AI Recommendations?
Tell us about your needs — we'll find the optimal solution.