Babel Street Unveils Babel BOX for Sensitive Data Search and Analysis

Babel Street Unveils Babel BOX for Sensitive Data Search and Analysis

Babel BOX Allows Organizations to Securely Fuse Sensitive Data Holdings with Publicly Available Information to Generate Actionable Intelligence

Babel Street, an advanced multi-lingual search and analytics software company, launched Babel BOX™ (Blended Onsite eXploitation). Babel BOX is a data synthesis engine that is deployed on a classified or private network to support sensitive data analysis. With Babel BOX, organizations can leverage Babel Street’s sophisticated linguistic algorithms and advanced analytics to explore data from internal repositories.

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Babel BOX Brings the Power, Speed, and Accuracy of its Multi-lingual Text Analytics Engine to Closed Networks for Sensitive Data Search and Analysis.

Customers can also integrate their proprietary data sets with Babel Street’s vast unclassified data sources, such as social media platforms, message boards, the deep and dark web, and traditional websites, in customers’ own controlled environment.

“Organizations, for a multitude of reasons, have sensitive data that cannot be shared with a public cloud-based or hosted solution,” said John Weaver, Babel Street’s Senior Vice President of Products.

John continued, “That data is highly valuable and contains great insights when the proper analytics can be applied to it.  Babel Street now provides a solution for this use-case. Babel BOX allows these organizations to leverage our world-class, supercharged text analytics technology to correlate and fuse sensitive data with publicly available information through a single tool, helping them identify patterns and risks.”

Key Features of Babel BOX

Advanced linguistic algorithms – search natively in over 200 languages leveraging Babel Street’s proprietary, patented cross-lingual search ontology

Open platform – integrate with customer tools and data sets so that all available data can be viewed through a single pane of glass

Scalable analytics – conduct data triage, analyze sentiment in 19 languages, detect trends and anomalies, set custom alerts, visualize data geographically, and collaborate with peers.

Stand-alone technology – operate behind the firewall without accessing the Internet

Unprecedented data access – ingest and integrate Babel Street’s vast data collections from over 40 unique sources and aggregated data sets.

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Recent studies (including CrowdFlower’s 2017 Data Science Report and Blue Hill Research’s 2015 Study) indicate that data analysts spend up to 80% of their time collecting, manipulating, and organizing data, leaving only 20% to decipher the data and report conclusions.

With Babel BOX, analysts can view all of their data, unbound by source, language, sensitivity level, and format, in a single platform.  This significantly decreases the amount of time spent transforming data while increasing the depth, breadth, quality, and accessibility of their analysis.

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Picture of Sudipto Ghosh

Sudipto Ghosh

Sudipto Ghosh is a former Director of Content at iTech Series.

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