AI Entertainment Discovery Engine

AI Entertainment Discovery Engine uses large-scale recommendation models and generative AI to match each viewer or listener with the most compelling movies, shows, music, and interactive content across devices. It continuously learns from behavior, context, and feedback to personalize rankings and suggestions in real time. This drives higher engagement, longer session times, and better content ROI for streaming and entertainment platforms.

The Problem

“Your catalog is exploding but users still can't find anything they want to watch”

Organizations face these key challenges:

Large and growing content catalogs where 70–90% of titles get little to no exposure or consumption

Home page and feeds feel “the same for everyone,” causing choice paralysis and short sessions

Manual curation and rule-based recommendation logic that doesn’t adapt to real-time behavior or context

Limited ability to measure which personalization strategies actually drive retention, upsell, and content ROI

AI Entertainment Discovery Engine

The Problem

Impact When Solved

The Shift

Technologies

Key Players

Real-World Use Cases

Building Recommendation Systems Using GenAI and Amazon Personalize

Foundation Model for Large-Scale Personalized Recommendation

Personalized Recommendation Impact Analysis for Streaming Platforms

Integrating Netflix's Foundation Model into Personalization Applications

Streaming Content Recommendation Systems