The Challenges of Deploying Real-time AI for Finance and How Open Source Can Help

Explore the challenges of deploying real-time AI for finance and discover how open source solutions can address these issues in this 43-minute conference talk by Nava Levy from Redis. Learn about the rising demand for real-time AI/ML use cases in financial services and the difficulties in scaling them reliably and cost-effectively. Delve into how open source software for machine learning operations (MLOps) and Feature Stores are helping to overcome these challenges. Examine case studies from FinTech companies using tools like open source Feast and Redis for real-time applications such as fraud detection and lead scoring. Gain insights into AI regulations, feature store implementations, and benchmarks in the financial sector, with numerous resources provided for further exploration.

The Challenges of Deploying Real-time AI for Finance and how Open Source can help - Nava Levy, Redis