Abstract: Techniques are described that include detecting customer personal information within any appropriate set of data, such as customer communications produced by customer-facing services offered by an organization. Once detected, the customer personal information may be tokenized within the customer communications, making the data appropriate for external systems, such as cloud-hosted applications. The disclosed techniques include a masking service that may be plugged into an on-premises pipeline of any customer-facing service that makes requests to an off-premises, cloud-hosted application. The masking service may apply rule-based detection and/or machine learning-based detection to detect both structured and unstructured customer personal information included in customer communications. The masking service may further tokenize or otherwise obfuscate or replace the detected customer personal information.

Abstract: Techniques are described that include detecting customer personal information within any appropriate set of data, such as customer communications produced by customer-facing services offered by an organization. Once detected, the customer personal information may be tokenized within the customer communications, making the data appropriate for external systems, such as cloud-hosted applications. The disclosed techniques include a masking service that may be plugged into an on-premises pipeline of any customer-facing service that makes requests to an off-premises, cloud-hosted application. The masking service may apply rule-based detection and/or machine learning-based detection to detect both structured and unstructured customer personal information included in customer communications. The masking service may further tokenize or otherwise obfuscate or replace the detected customer personal information.

Abstract: Techniques are disclosed to facilitate an improved data query system for an elastic search cluster. An ingestion framework receives data from several sources, indexes this data, which is then stored as indexed data files across several data nodes in the elastic search cluster. The system also utilizes a query template management system, which matches a query to a particular query template based upon various parameters. The matched query template specifies one or more relevancy factors that are applied to the query to cause the elastic search cluster to perform the search in a specific manner. In this way, the query templates allow for search results to be tailored in a highly customized manner based upon the desired characteristics that are used to match, or trigger, the specific query template. The relevancy factors can also be dynamically updated to improve the search results over time.