Recommendation Engine

  Personalization   Increase in revenue   Increase user engagement and retention.   Product Discovery.   Any cloud platform.   Plug and play.

Why Recommendations?


Core AI/ML Engine

Recommendation as the Service

Platform independent data Model

Analytics & MIS
Recommendation Engine Techniques


Personalized Content Bank

Personalized Search




Continue watching

Recommend next

Time based Recommendations

Available now

Favorite channels

Watch again

User Action based

Based-on Genres/Sub-genre/Features

Rail reordering

Coming soon

Régional content

Cold start

Personalized Genre/languages

Recommendations feedback

Series vs episode Recommendations

Many more

Recommendation Engine Applications

Online marketplaces employ recommendation engines to propose products to users based on their browsing and purchase history. This personalized approach enriches user experience, fosters greater customer engagement, and drives sales growth.
Video and music streaming platforms leverage recommendation engines to suggest relevant movies, TV shows, or songs, tailoring the offerings to users’ viewing and listening habits. This ensures sustained user involvement and facilitates the exploration of fresh content.
Social networking sites rely on recommendation systems to propose friends, groups, or pages of potential interest to users, thereby fostering heightened engagement and expanding their social connections.
News portals, blogs, and article platforms implement recommendation engines to provide users with personalized content based on their individual interests and reading history.
Travel websites and hotel booking platforms utilize recommendation engines to propose pertinent destinations, accommodations, and travel itineraries that align with user preferences and past bookings.
Digital advertising platforms harness the power of recommendation engines to display targeted ads to users, grounded in their behavior and interests. This results in heightened ad relevance and increased click-through rates.
Job search platforms employ recommendation systems to suggest relevant job openings to candidates and match them with potential employers based on their unique skill sets and experience.
Food delivery platforms rely on recommendation engines to propose restaurants and dishes based on users’ prior orders and preferences.
Educational platforms utilize recommendation engines to offer tailor-made learning paths and propose pertinent courses or study materials in line with a student’s knowledge level and learning style.
Health and fitness apps leverage recommendation engines to provide personalized workout plans, nutrition tips, and wellness suggestions based on users’ fitness goals and health data.
Video game platforms make use of recommendation engines to suggest new games or in-game items that align with users’ gaming history and preferences.
Targeted Personalized marketing and be achieved using a recommendation engine, this will upsell and enhance user engagement with optimum ROI.
Targeted Personalized marketing and be achieved using a recommendation engine, this will upsell and enhance user engagement with optimum ROI.
In summation, recommendation engines play a pivotal role in elevating user experiences, fostering heightened customer engagement, and propelling business expansion across a wide spectrum of industries and platforms.

Want to integrate
Recommendation Engine.