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Content Extraction

The type of data available and the type of answers sought after may vary between different situations.  In all cases,  the answers must be delivered quickly and accurately - many times the same question may be asked with the answer returned required to take into account new developments or added data.  There is no one-size-fits-all solution to these problems.  However, proven techniques may be used again and again to achieve results.

Our application of applied research methods brings optimized data extraction to a commercial level.  Leveraging existing technologies and software of the NeuStratos platform, it is possible to design and deploy custom analysis on massive datasets in a timely manner.

Existing capabilities in the NeuStratos platform include

  • Web based data set management and analysis interface
  • Web based graphical reporting
  • Automated PDF report document generation
  • User security and authentication management
  • User secure messaging and collaboration

Customized algorithms are developed depending on the data available and the questions being asked, but may leverage applied research efforts including

  • Distributed analysis across many compute nodes
  • Trend analysis and event identification using artificial neural networks and concept mapping
  • Reactive predictions based on historical data and external RSS feeds
  • GPU computing to realize massive computational capability for numerically intensive data sets

Existing COTS technology is unable to provide this level of achievement, as it is unable to adapt to very specific questions at hand.  Often, the application of such solutions requires heavy adaptation and often realizes inefficient use of compute resources, which are not being used in ways which optimize computation for the problem being solved.  The direct application of applied research methods is a step above the competition, and raises the bar on COTS technology.