- Quality and Quantity
- Our database contains hundreds of records that have been thoroughly verified to ensure the highest quality results. We scrutinize new entries thoroughly to reduce false positives and ensure customer satisfaction.
- Context Exclusions
- False positives create a bad user experience and upset customers. Unfortunately, they are difficult to completely avoid. In order to help reduce false positives, the database comes with a list of contextual exclusions. Contextual exclusions are words that contain profanity but should not be filtered. Examples include peacock and assume.
- Periodic Updates
- We work hard to ensure that our database contains as many words as possible. Updates to the database help address both the specific needs of our existing customers and the general needs of our future customers.
- Built for the Future
- As the marketplace becomes more global, there is an increased need for an internationalized filtering solution. Our database is built with this goal in mind. Each record contains locale information and the database is formatted using Unicode. This allows the addition of new records in other languages, depending on customer requirements.
- Regular Expressions
- Users are smart but our database is smarter. With other solutions, getting around a filter is as easy as using the space bar (r i g h t?). Our database contains a comprehensive list of regular expressions that catch complex attempts to circumvent the filter.
- Alternate Spellings
- In addition to the word itself, our database contains a large list of alternate spellings. These include phonetic variations as well as common slang and Internet spellings of the word. These alternate spellings assist applications in preventing users from attempting to circumvent the filter.
- Rating System
- The database provides a rating system that identifies the severity of each record. This allows customers the flexibility to customize their level of filtering according to their specific needs.
- Category System
- The database uses a category system that classifies words into groups. This further increases the flexibility of customers to control their level of filtering. Examples of categories include 'Swear', 'Slang', and 'Racial slurs'.
- Updates
- Purchasing the database entitles customers to released updates of the database. Details regarding updates are specified in the Inversoft License Agreement.















Overview
Features