Hands-on: Real-time AI recommendations with Momento Functions
Delivering personalized content in real time is critical for modern media and entertainment platforms, whether it's keeping sports fans engaged with live updates or surfacing the next binge-worthy series. In this hands-on workshop, you'll build and deploy a production-grade recommendation system step by step. Using AI techniques like embeddings and vector search, you'll transform raw content into personalized recommendations and package the pipeline as lightning-fast APIs with Momento Functions.
By the end, you'll have three live APIs - embed, search, and recommend - ready to plug into any app or workflow. No prior experience with AI or Rust required.
You can follow along with the complete code samples and instructions on GitHub here.
Adam Brown
Co-Founder & CTO
Mux
Adam Brown co-founded Mux in 2015 and leads technology and architecture for the developer-first video infrastructure platform. With deep roots in video technology, Adam has built high-performance encoding systems, low‑latency live streaming pipelines, and scalable cloud video infrastructure, including during his time at Zencoder and Brightcove, with additional experience in VR rendering at Otoy.
Known for merging engineering rigor with developer empathy, he’s focused on enabling seamless, scalable video delivery and real-time analytics through API-first products like Mux Video and Mux Data.