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Discover how Swiggy, India's leading quick commerce platform serving 13 million users across 653 cities with 196,000 restaurant partners and 17,000 SKUs, built a secure and scalable AI platform capable of processing millions of predictions per second. Learn about the comprehensive tech stack implementation including Apache Kafka for real-time streaming, Apache Spark on Databricks for analytics and machine learning, and Apache Flink for stream processing. Explore the Lakehouse architecture built on Delta that ensures data reliability, and understand how Unity Catalog enables centralized access control and auditing across the platform. Examine the critical AI applications powered by this infrastructure, including demand forecasting, route optimization, personalized recommendations, predictive delivery SLAs, and generative AI use cases. Gain insights into building data platforms at scale with focus on cost efficiency, simplicity, and speed that enable seamless support for millions of users and diverse AI applications in the quick commerce industry.
