Automated Collection & Processing

ZyLAB eDiscovery software leverages automation and best practices to collect an exhaustive data set and then methodically whittle it down to an optimized review set that is proportional to the matter. We apply our highly-advanced technology to detect and assimilate complex files, cull content, prep it for thorough legal analysis, and continually refresh the collection with new files.

See our eDiscovery collection and processing in action! Please click here to receive a demo

Features & Functions of our ediscovery collection & processing

  • Automatic, incremental collections of new data based on the administrator’s defined schedule and frequency
  • Inventory reporting
  • IT source mapping
  • Automatic semantic indexing of the data collection and auto conversion to uniform and searchable format
  • Automatic culling to unpack compound files (e.g. zip, rar) and nested e-mails and their attachments
  • Support for multiple email formats including eml, nsf, pst, and their attachments
  • Integrated multi-directional OCR
  • Advanced detection and processing for bitmaps, handwriting, and foreign languages
  • Extraction of embedded objects
  • Automatic removal of NIST file matches
  • Automatic de-duplication
  • Automatic language recognition and option for automatic machine translation
  • Automatic extraction of metadata
  • Automatic recognition and processing of OCR bitmaps
  • Automatic flagging of “outlier files” requiring manual attention
  • Automatic coding, categorization, foldering and clustering based on defined search engine behavior and results
  • Exception workflow

Benefits of automated ediscovery collection & processing

  • Reduces need for human intervention
  • Reduces chance for errors
  • Minimizes interruptions
  • Lowers eDiscovery costs
  • Automatic handling for complex files
  • Greater process control and defensibility
  • Reports and logs to prove chain-of-custody
  • Maintains sampling and QC options

Return to ZyLAB eDiscovery & Production System Overview