How an Open, Scalable and Secure Data Platform is Powering Quick Commerce Swiggy's AI
Description
Swiggy, India's leading quick commerce platform, serves ~13 million users across 653 cities, with 196,000 restaurant partners and 17,000 SKUs. To handle this scale, Swiggy developed a secure, scalable AI platform processing millions of predictions per second. The tech stack includes Apache Kafka for real-time streaming, Apache Spark on Databricks for analytics and ML, and Apache Flink for stream processing. The Lakehouse architecture on Delta ensures data reliability, while Unity Catalog enables centralized access control and auditing. These technologies power critical AI applications like demand forecasting, route optimization, personalized recommendations, predictive delivery SLAs, and generative AI use cases. Key Takeaway: This session explores building a data platform at scale, focusing on cost efficiency, simplicity, and speed, empowering Swiggy to seamlessly support millions of users and AI use cases. Talk By: Akash Agarwal, Principal Engineer, Swiggy ; Vasan Vembu Srini, Sr Solutions Architect, Databricks Here’s more to explore: Production ready data pipelines for analytics and AI: https://www.databricks.com/solutions/data-engineering The Big Book of Data Engineerin…
Description from YouTube. Full content on the video page.
More from Databricks
ReleasesDatabricks launches across the Data + AI stack in 90 seconds
Databricks announced LTAP to unify lakebased and lakehouse data, eliminating ETL and enabling a single copy of data for analytical and operational needs. They also introduced Unity AI Gateway for governance, Genie Ontology for enterprise knowledge graphs, and open-sourced Omniant for managing multiple coding agents.
ReleasesIntroducing Omnigent: The Ultimate Meta-Harness for AI Agents
Omnigent is a new open-source meta-harness for AI agents that provides a unified interface for composition, control, and collaboration across multiple models and agent workflows. It enables stateful, data-centric policies for guardrails and allows real-time sharing and steering of live agent sessions with teammates.
NewsHow DEFRA and Natural England Accelerate Peatland Restoration with AI and Databricks
DEFRA and Natural England utilize AI and Databricks to accelerate peatland restoration by automating the mapping of peatland features and peat dams across England. This technology significantly reduces the time required for mapping, enabling faster identification and restoration of these crucial carbon-storing habitats.
NewsAI Stack Explained in 3 Layers (LLM, Agent Harness, Omnigent)
The AI stack now includes a third layer, the meta harness, which sits above individual agent harnesses. This meta harness, exemplified by Databricks' open-sourced Omnigent, allows for routing queries to appropriate agents and orchestrating tasks across multiple agents, enabling seamless interaction and context sharing between them.
NewsWhat’s coming next to Free Edition
Databricks announces the availability of Genie, GPUs, Agent Hooks, Lakehouse, and Lake Flow Designer on its Free Edition. This update provides virtually all of Databricks' production platform features for free, enabling users to learn and build data and AI projects.