Agenda

› Opening

Jim Dowling

› Beyond Feature Retrieval: Transformations and Composition in Feature Views

Jim Dowling

› Feature Serving Beyond RAM

Roman Grebennikov

› Taming the ML Firehose: Scaling Feature Consistency

Paarth Chothani · Chirag Agrawal

› Designing an Efficient Real-Time Feature Store at Zomato

Nilotpal Pramanik · Yash Shukla

› To be announced

› OpenAI-Compatible Agents with Governed Context: Feast, MLflow, and OGX

Nikhil Kathole

› Accelerating and Protecting Payments with Real-Time Data for ML

Vitalii Zhebrakovskyi · Antonio Momblan

› Real-Time Features without Streaming using RonDB

Mikael Ronström

› Random Access Parquet: Serving Point Queries Straight from the Data Lake

William Edwards

› Review Loops for Agents Using Real-Time Context

Will Burstein

› Online, Offline, n-Chaos: From Stored Features to Executable Definitions

Tom Kaltofen

› The Benchmark to Production Gap: Frontier Evaluations for Adaptive Personalization

Rishabh Mehrotra

› Feast vs Chronon: Why Not Both?

Francisco Arceo

› From Daily Batch to Real Time: An NRT Generative Recommender with Chronon

Pengyu Hou · Yuli Han

› How to Know You've Outgrown Your Real-Time Feature Store

Aaryan Gupta

› Semantic IDs for Recsys with Chronon

Varant Zanoyan

› Building Real-Time Context for Data Agents That Improve ML Models

Elliot Marx

› Wrap-up

Jim Dowling