Elasticsearch's context suggestions feature enhances the functionality of the completion suggester by allowing users to apply filters to suggestions based on specific contexts, such as type or geographic location. This approach addresses the need for more controlled and relevant suggestions by enabling filters that consider various scopes defined by the user. For instance, in an e-commerce setting, suggestions can be filtered to show only products within a selected category, or in a restaurant finder, suggestions can be limited to venues within a certain proximity of the user. This is achieved by combining multiple context suggesters, such as type and location, to refine results, thereby creating more customized and precise user experiences. The implementation involves setting up mappings and indexing documents with context information, while Elasticsearch internally uses prefix graphs to handle these contexts, including converting geographic points into geohashes for spatial suggestions. This flexible system supports numerous use cases by allowing multiple contexts to be applied simultaneously, offering a powerful tool for creating tailored suggestions in various applications.