Abstract: Among other techniques, techniques for providing feedback associated with personally identifiable information (PII) to a customer that is a member of an industry are described. The feedback includes a comparison with dynamic industry state. A system utilizing these techniques can include a continuous initially personally identifiable information (IPII) destruction engine; an IPII feature extraction engine coupled to the continuous IPII destruction engine; a bit labeling engine coupled to the continuous IPII destruction engine; a classified and interpreted IPII attribute instance bits datastore coupled to the bit labeling engine; and an auto-meta comparator feedback engine coupled to the classified and interpreted IPII attribute instance bits datastore.

Abstract: Ingesting data from a plurality of data sources. Converting the data into a plurality of vectors, wherein each vector represents a respective object of the data. Comparing the plurality of vectors with each other. Determining a distance between the plurality of vectors based on the comparison. Receiving a query. Automatically determining a set of candidate matches based on the query and the determined distances between the plurality of vectors based on the comparison. Resolving the query based on matching one or more portions of the query with the set of candidate matches.

Abstract: Among other techniques, techniques for machine learning-based entity resolution are described.

Abstract: Among other techniques, techniques for providing feedback associated with personally identifiable information (PII) to a customer that is a member of an industry are described. The feedback includes a comparison with dynamic industry state. A system utilizing these techniques can include a continuous initially personally identifiable information (IPII) destruction engine; an IPII feature extraction engine coupled to the continuous IPII destruction engine; a bit labeling engine coupled to the continuous IPII destruction engine; a classified and interpreted IPII attribute instance bits datastore coupled to the bit labeling engine; and an auto-meta comparator feedback engine coupled to the classified and interpreted IPII attribute instance bits datastore.

Abstract: Among other techniques, techniques for machine learning-based entity resolution are described.

Abstract: Among other techniques, techniques for providing feedback associated with personally identifiable information (PII) to a customer that is a member of an industry are described. The feedback includes a comparison with dynamic industry state. A system utilizing these techniques can include a continuous initially personally identifiable information (IPII) destruction engine; an IPII feature extraction engine coupled to the continuous IPII destruction engine; a bit labeling engine coupled to the continuous IPII destruction engine; a classified and interpreted IPII attribute instance bits datastore coupled to the bit labeling engine; and an auto-meta comparator feedback engine coupled to the classified and interpreted IPII attribute instance bits datastore.