Tabular data enrichment involves leveraging external data sources to enhance the content of a source table through automated pipelines. This paper proposes a service model that standardizes API definitions for accessing specialized, single-task services, transforming them into modular components for seamless integration into various workflows. This approach facilitates dynamic composition and execution of services, providing flexibility to meet diverse enrichment needs while lowering the expertise barrier for users. The model supports the extend by linking paradigm, reconciling and linking relevant columns in a source table to external datasets, typically knowledge graphs, to enrich the table with new content. Grounded in REST and microservices principles, the service model supports a lightweight, modular architecture and complies with the W3C reconciliation API for data matching, ensuring interoperability.