What is Scraawl TxT®?
Document and media exploitation tool
Scraawl TxT® is a search and analytics toolbox that leverages advanced machine learning techniques to facilitate knowledge discovery from unstructured text. Scraawl TxT® offers context-aware multi-source text information extraction and extends current search and analysis capabilities by enabling the exploration of large bodies of text. Analysts can quickly search and explore large volumes of unstructured text; identify the most relevant and valuable information; and discover and monitor interesting patterns of topics, opinions, and/or interactions.
What can Scraawl TxT®do for you?
Leverage natural language processing and graph analytics for data exploitation
Scraawl TxT® provides analysts with an interactive dashboard for scalable discovery from scattered, heterogeneous datasets (both structured and unstructured) such as news articles, reports, blogs, documents, comments, chat transcripts, SMS, and e-mail. With Scraawl TxT® users can perform multidimensional search for key actors, discover topics, events, and relationships of interest, topic clusters, and compare analysis results based on context variables such as time, authorships, sentiment, and source. With Scraawl TxT®, users can perform multidimensional search for key actors; discover topics, events, and relationships of interest; and compare analysis results based on context variables such as time, author, sentiment, or source.
Advanced Text Analytics
All the analytics you’ll ever need, at your fingertips, anytime, anywhere
A web-based visualization and analytics dashboard for easy access anytime, anywhere, and on any device.
A scalable data ingestion pipeline to index and store large volumes (terabytes) of content and scanned documents in multiple languages.
Advanced full-text search options in combination with rich Boolean logic and interactive filters to search and explore data.
Detection and resolution of named entities in the text, such as organizations, people, and locations.
Graph to explore and search for relationships between entities within and across documents.
Common themes and topics of conversation across your repository of documents that can be used for filtering and analysis.