Philter redacts sensitive information from text and PDF documents.
Philter redacts removes sensitive information, such as Personally Identifiable Information (PII) and Protected Health Information (PHI), from text and PDF documents.
Using state of the art natural language processing, Philter analyzes text and PDF documents for many types of sensitive information to redact, mask, encrypt, hash, or replace with random values. You can apply conditional logic based on attributes such as the type or content of sensitive information to have fine-grained control over how sensitive information is identified and manipulated and to generate alerts.
Some of the types of information Philter can identify include: Ages, Bitcoin Addresses, Cities, Counties, Credit Cards, Custom Dictionaries, Custom Identifiers (such as medical record numbers, financial transaction numbers), Dates, Drivers License Numbers, Email Addresses, IBAN Codes, IP Addresses, MAC Addresses, Passport Numbers, Persons Names, Phone and Fax Numbers, Physician Names, SSNs and TINs, Shipping Tracking Numbers, States, URLs, US street addresses, VINs, Zip Codes
Philter's API provides an endpoint for submitting text and PDF documents and receiving back the filtered text or document. Philter's UI dashboard provides easy access to test Philter's configuration and manage filter profiles. Open source API clients are available.