Swiggy Uses 350+ Features and Multi-Task MLP to Predict Customer Lifetime Value

Leela Kumili — Wed, 02 Sep 2026 13:55:00 GMT

Swiggy developed an in-house predicted lifetime value model using more than 350 pre order features and a multi task MLP for Food and Instamart. Adding order count as an auxiliary task reduced model parameters by 63% while improving predictive performance. The pLTV signal is used with Google Target ROAS bidding to optimize customer acquisition.

By Leela Kumili

AWS Introduces Specification-Driven Composition for Flexible Data Workflows

Leela Kumili — Wed, 26 Aug 2026 14:18:00 GMT

AWS describes a specification-driven approach for composing flexible data workflows by separating intent from processing logic. Architecture uses declarative specifications, reusable processing capabilities, and validation before execution. AWS reports that the approach can reduce dataset onboarding from weeks to days while supporting traceability, versioning, data classification, and governance.

By Leela Kumili

InfoQ - Software Engineering

Swiggy Uses 350+ Features and Multi-Task MLP to Predict Customer Lifetime Value

AWS Introduces Specification-Driven Composition for Flexible Data Workflows