Swiggy is using Snowflake as a unified data foundation to support analytics and decision-making across its food delivery, Instamart and Dineout businesses, with the platform helping accelerate some data workloads by up to 96%, Snowflake said.
As Swiggy expanded across multiple businesses, the company faced challenges in extracting insights from fragmented data and supporting peak workloads. It also wanted to provide employees with self-service access to data while reducing reliance on central data teams.
Swiggy has established a central analytical layer on Snowflake using Apache Iceberg. According to Snowflake, the move has improved the company’s slowest data workflows by 90% to 96%. Its heaviest queries have been reduced from about two hours to 15 minutes, while data processing that previously took six hours can now support near real-time decision-making.
The changes are being applied across several functions. Marketing teams can build and launch targeted campaigns within their own tools, while product engineering teams use standardised metric definitions to assess experimental features before release through an in-house platform running on Snowflake.
Operational teams can monitor service quality metrics in real time to identify areas for improvement in delivery logistics. Finance teams, meanwhile, have access to workload-level visibility into technology expenditure.
The data environment also incorporates role-based access controls, column masking and row-level security, allowing internal teams and external partners to work with data while maintaining access restrictions.
Snowflake said its governance framework also extends these controls to AI-powered agents and applications. AI agents can operate within the same permission boundaries, use short-lived credentials and maintain audit trails similar to those required for human users.
“At Swiggy, data is valuable only when it reaches the person who can act on it, whether that is a city sales manager, restaurant owner or delivery partner,” said Madhusudhan Rao, chief technology officer, Swiggy. “With Snowflake, we are making trusted, governed insights easier to access while ensuring that every user and AI agent operates within the same permissions and audit framework.”
Vijayant Rai, Managing Director, India, Snowflake, said companies increasingly need to enable employees to access data without routing every request through a central data team.
“With Snowflake, Swiggy has built a centralised, governed data foundation, consistent controls, and an AI framework that holds agents to the same standards as people,” Rai said. “This approach is helping Swiggy create a path toward more capable and accountable AI agents.”