Recommender System

That Delivers Accurate Real-Time Predictions At Scale

Vizle

It’s a recommendation engine we developed for leveraging logical analysis with the help of technology in improving user personalization, recommendations, actionable insights, marketing automation and more. Vizle helps to apply unsupervised machine learning techniques to datasets accurately and generates recommendations based on the available information, seamlessly. For instance, Sigmaways recommender allows a scalable search & suggestions based on multiple attributes in media like Genre, Popularity, Timeline, ratings etc. so that users can access the platform without any explicit input.

Personalized Experience

Easy To Integrate Recommender System

User API

Vizle offers user API that supports
  • User Register
  • User Clear
  • User History

Recommendation API

We offer recommendation specific API that supports
  • User-Specific Recommendation
  • Language Filtering
  • Trending Recommendations To First-Time Users

Event API

Event-specific API that supports
  • Product Add
  • Purchaser
  • Ratings
  • View

Unsupervised Learning

Content-based filtering using kNN algorithm
  • User Register
  • User Clear
  • User History

Why Vizle?

An Autonomous System Delivering User-Centric Experience

Media Recommendations

Based On Metadata attributes such as genre, cast, program, and schedule delivering relevant user experience across touchpoints

External Sources

Data enrichment through third party sources like IMDb supported by AI

Contextual Search

Real-time search personalization backed by a ranking algorithm

User Information & Real-Time Insights

Suggestions based on user preferences and demographic information, providing real-time user activity insights for smart user engagement

Churn Prevention

Subscriber prediction and churn reduction with integrated machine learning models

Media Recommendations

Based On Metadata attributes such as genre, cast, program, and schedule delivering relevant user experience across touchpoints

External Sources

Data enrichment through third party sources like IMDb supported by AI

Contextual Search

Real-time search personalization backed by a ranking algorithm

User Information & Real-Time Insights

Suggestions based on user preferences and demographic information, providing real-time user activity insights for smart user engagement

Churn Prevention

Subscriber prediction and churn reduction with integrated machine learning models

Unmatched Outcomes

Accelerated Succes Rates

Decreased Bounce Rate

Increased
Time-Spend

Added Value
For Subscriber

Increase In
Revenue Rates

Engineer Your Digital Tomorrow, Today