InFact is intended to enable professional analysts and researchers to accurately uncover facts and relationships within text documents. InFact parses the structure of each sentence and is designed to "understand" the sentence components, such as which words are nouns and which are verbs. Combinations of nouns, verbs, and other sentence components connote relationships, actions, or facts and are stored in a searchable database structure. Because InFact is designed to understand the grammar, syntax, semantics, and linguistic structure of each sentence, InFact's query syntax can be used to search for very specific relationships, actions, or facts. Infact's query language is designed to enable analysts to formulate searches that not only search for a particular relationship, action or fact, but also understand action directionality (i.e., company A bought company B, and not vice versa).
In addition, users of InFact can search for relationships involving entity types (e.g., search for any person or organization that was involved in a particular action, not just a particular person), and constrain results based on Boolean combinations and metadata constraints (e.g. the document was published between 1995 and 2005, and the action happened in either North America or Europe).
InFact is designed to ingest millions of documents and update its search database with no downtime. A distributed and flexible architecture can be configured to meet specific organizational needs whether documents reside in legacy database systems, the Web, institutional news feeds, or other enterprise systems. Customers can incorporate proprietary ontologies (with simple or multi-parent taxonomies, synonyms, acronyms, and new entity type assignments), endowing the InFact system with knowledge of a vertical domain. A Java Search API enables client or server side development, embedding of all InFact functions in other systems, or integration with third-party visualization tools. InFact is built on case insensitive natural language parsing technology.InFact provides interactive relationship-based reports. Users can search for precise concepts and action patterns and then sort results using multiple mechanisms and criteria, such as relationship frequency, geographical locations, or a timeline. Users of InFact can generate cross-document reports and summaries that are dynamically hyperlinked to original source documents, providing an innovative way of navigating document databases. Reports can be shared in a collaborative environment or exported to a central relational database system. In addition, customers can visualize links through a third-party visualization tool.