Chalk is a platform designed to simplify the complexities of real-time machine learning (ML) pipelines by abstracting the intricacies of data pipelines, caching, and serving infrastructure. It allows ML teams to focus on feature engineering through declarative feature definitions and programmatic feature management, enabling seamless entity relationships and real-time feature computation with composite keys. Chalk supports incremental processing and smart caching strategies to maintain data freshness without over-engineering, while also allowing data teams to connect new data sources quickly and independently. Leveraging existing infrastructure, Chalk runs within a user's VPC, ensuring data isolation and compliance. By reducing dependencies and streamlining operations, Chalk empowers teams to develop, test, and deploy ML models rapidly, enhancing productivity and innovation in data-driven decision-making.