Phase IV - Processing, Review and Analysis

Following the comprehensive data collection exercise, data is often uploaded to a secure, non-networked, server for processing. Espion maintain a dedicated computer laboratory at our Dublin HQ for this purpose.

The Forensics Laboratory is certified to the ISO 27001 standard for information security, ensuring that our client’s data remains safe and secure at all times.

Espion also operates a mobile laboratory whereby we perform the data processing phase on-site at a client office where necessary.

The primary software tool used to analyse and process data is the Clearwell Systems Electronic Discovery platform. Rated as a “Strong Positive” (highest possible rating given) in Gartner’s 2009 E-Discovery MarketScope Report and voted a Top 5 E-Discovery Software Provider by the 2008 Socha-Gelbmann survey, the Clearwell E-Discovery Platform is the first enterprise-class e-discovery solution that manages all legal matters, regulatory inquiries, and corporate investigations in a single application.

The Clearwell e-Discovery platform provides legal teams a number of features to expedite the document review process including:

• Quick Search: delivers Google-like search capabilities to the entire corpus for a case, allowing for a “first look” at a case and perform rapid early case assessment.
• Relevance Rank: consider the unique properties of email and documents to display the most relevant documents or email discussion threads first.
• Discussion Threads: dynamically link together all related messages into chronological threads that capture the entire discussion, including all replies, carbon copies, and forwards.
• File Analytics: identify duplicate files that may be attached to multiple emails or may be “loose” on a user’s hard drive.
• File Tagging: Tag files as relevant, privileged, not relevant etc. redact files, watermark files.
• Case Organisation: Divide the review workload between a team, and logically organise files or emails of interest for further review.

Clearwell helps reduce a large dataset to a much smaller, more relevant dataset. Many organisations simply process all collected data and cull-down by date range, keywords, and hit counts.