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Dec 28, 2025 Varant Zanoyan, Co-founder and CEO of Zipline AI, and Nikhil Simha Raprolu, Co-founder and CTO at Zipline AI, delve into the evolution of AI infrastructure. They share insights on the compute-first approach of Cronon that emerged from Airbnb, emphasizing real-time features over traditional storage models. The duo explains the complexities of orchestrating signals and pipelines, the challenges of point-in-time correctness, and the importance of governance. They also discuss how Cronon integrates embeddings and real-time workflows, reflecting on its open-sourcing journey with Stripe.
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Cronon Born From Fighting Payments Fraud
- At Airbnb the early Cronon versions were built to fight payments fraud and enable rapid iteration for adversarial use cases.
- Teams needed to engineer features in hours because fraud patterns required very fast responses.
Models Need Thousands Of Signals
- Production ML pipelines require hundreds to thousands of simple
Productize Complex Data Tech For Adoption
- Productize and abstract the underlying big-data tech so non-experts can adopt systems like Chronon.
- Provide an open-core model to avoid vendor lock-in while easing enterprise adoption.