This multilingual social media solution provides customers with the unique capability to address a number of use cases, such as: border security, threat assessments, real-time situational assessment based on sensor feeds, environmental assessments, insider threat assessments and a myriad of other customized configurations specific to a customer need.

The Looking Glass™ solution pulls and fuses data from open source, commercial (business, financial and others) and the dark net, into a framework that permits users at various levels of experience to gain knowledge and begin to anticipate future events.  It is designed to empower users to reliably and instantly detect insights for making timely decisions.

Our solution ingests data from other sources in addition to crawling the internet for specific data relative to the use cases desired by the customer.  Sources range from government websites and corporate webpages to news media and web blogs like Wikipedia to social media platforms such as Twitter, Facebook, or YouTube. No matter the format, Looking Glass™ can pull in content for further analysis by treating each source as a sensor.

After collection, information extracted from each data source passes through a multilingual text analysis tool in order to extract the entities contained within. These entities—names of persons, places, or things—are key to creating a Knowledge Web, or a map of relationships between known, linked entities. By parsing out this information in the content’s native language, Looking Glass™ reduces the probability that errors will be made due to poor translation into English or another language desired by the customer.

Looking Glass™ differs from other entity extraction and relationship solutions by leaving the construction of relationships completely to the ‘mind’ of the machine. The information contained in the Knowledge Web is formed through empirical and objective means, because the text analytics are being performed without interference from subjective or biased human editors. Only after assembly do humans become involved; they can search this codified data source to find relationships that were previously unseen or unknown and are constantly being updated and refined as more information is fed into the system.

Through use of this transparent work model, Looking Glass™ is intended to be used as a base knowledge store from which predictive analytics can stem. As the web becomes ever more populated and technologies ever more complex, Looking Glass™ will cut through the noise to uncover the relationships that matter most.

Looking Glass™ is available now and can be tailored to your specific needs.

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