Cyberglobes provide a state-of-the-art system for law enforcement to prevent criminal activities

Our system scans and analyzes the data sources to discover criminal activities, such as drug trafficking, financial crimes and fraudulent activity, Our prevention technology covers the widest range of your sources. We preform cross-references between several types of information which are then available in a friendly visual display.

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Discover new insights from the existing information set in your organization

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Our engine infrastructure extracts anomaly activities comprehensively

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Sentiment Analysis: Our fusion system is equipped with text analysis combining natural language processing (NLP) and machine learning techniques to assign weighted sentiment positive or negative scores to text content.

Popular Trends: Exposes Popular Topics from Geographic Locations. Such viral phenomena is interesting to intelligence analysts when the event has a geographic significance.

Speech to Text (STT): The system makes it possible to convert speech from Audio and film to written text in a variety of languages, for quick content comprehension and for speech analytics.

Named-entity recognition (NER): AI information extraction seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as names, organizations, locations, time expressions, quantities, money and more, this allows to filter large amounts of data by topic and category

Advanced image analysis capabilities: The system has an advanced image analysis capability consisting of a number of analytics engines that include:

a.Optical character recognition (OCR)

b.Automatic Face Detection

c.Image Entity extraction: The system has the ability to detect objects such as glasses, hats, cars in pictures as well as feelings such as happy or sad people in the picture

Displays results visually: activity timelines, on pie charts, and displaying relationships with Visual Entity Relationship Graphs (VLN).

Tools and features

Text analysis including semantics, entity extraction, and words cloud

Determinates top influence and leading public opinion in conversation content

Graphical relationship map, exposing imposter profiles by making links between different social media outlets

Visual presentation on a map for content that indicates a place
(by reverse geo text)