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

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

Real-time AI/ML use cases for Financial Services are on the rise, but deploying them at scale reliably and cost effectively is challenging. In this talk we will see how open source software for machine learning operations (MLOps) and Feature Stores in particular, are helping address these challenges. We will also explore a few case studies in production, in which tools such as open source Feast together with open source Redis are deployed in FinTech companies for real-time use cases such as fraud detection and lead scoring.

Check out the links for resources mentioned in Nava’s talk:

-AI and Open Source adoption in FinServ:

-AI regulations and frameworks in general and for finance:

-Feature Stores articles

-Getting started tutorials with Feast and Feathr open source feature stores:

-Benchmarks

-Featured case studies and use cases mentioned in the talk:

  1. The Linux Foundation
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