Structured data about entities may exist across tables or datasets with unique schemas and that cannot be joined using explicit linking keys. However, ML and other applications may require context enrichment wherein features are extracted by joining information across tables without keys. To make this process less tedious, Sahanna Suri and collaborators have released Ember, a public API for a no-code context enrichment system that can be applied to a wide variety of tasks and domains with minimal configuration. Ember enables keyless joins by constructing an index using Transformers that generate task-specific embeddings. Users provide Ember with a base data source, auxiliary data source, and set of examples of related records and receive related records from the auxiliary data source for each base record.