The BIA ESI Management Model is a system used by corporations for over 6 years where data for legal matters is re-used matter over matter where possible to save time and money.

BIA has leveraged its powerful proprietary e-discovery data management engine, making digital evidence cataloging, indexing, analysis and deployment simple.

 

Designed to simplify and automate discovery obligations, the BIA ESI Management Model is a data re-use and tracking system that operates on a grid architecture and stores critical information in a centralized database.

• Maintains Chain-of-Custody (COC)
• Intelligent filters reduces duplicate, irrelevant and unnecessary documents by 85%
• Special automated analytics combines with advanced human review
• Retains high-level pre-tagging and filtering
• Possesses knowledge of thousands of file formats and system types
• Supports Unicode, double-byte character and legacy character sets
• Ability to perform high capacity, multiple and simultaneous productions
• Capacity to track document lifecycles using any know fields
• "Pristine sets" are cataloged and stored in a secure Central Evidence Repository

 

The BIA Analytics team works to eliminate non-responsive files thus reducing review costs through presumptive tagging when a working copy of potentially responsive documents is deployed for legal review.  All production sets are created from central evidence repository to ensure document integrity and tracking while data is stored in a Client's Centralized Evidence Repository managed by BIA and most often, reused matter over matter.

DEDUPLICATION

In order to reduce the number of files delivered for review, BIA TotalDiscovery™ implements comprehensive de-duplication and known file formats (KFF) strategies.

 

Using a combination of cryptographic hash functions and document metadata, TotalDiscovery™ detects duplicate files within a set of data. Duplicates can be identified on a per-custodian or cross-custodian basis, depending on the needs of the client.

 

A recent study of de-duplication strategies revealed that, on average, one in five files are identified as duplicates within a single custodian, and two in five are duplicates across all custodians. A BIA internal audit of a random sample of nearly 60 million documents processed by BIA TotalDiscovery™ identified nearly one in three files as single-custodian duplicates, and nearly one in two files as cross-custodian duplicates - in both cases, exceeding the rates found in the study by between ten and twenty percent.

 

How do BIA's efforts correlate to savings? If you consider a typical data set of 1 million documents, at a cost of $1 per document, BIA's optimized de-duplication strategy can yield a potential savings of between $100,000 and $200,000.

 

BIA's KFF strategy is to use the National Software Reference Library (NRSL) Reference Data Set (RDS), which is a public dataset that contains identifying information about files that make up software packages. This public dataset contains metadata on computer files with the ability to identify files and their locations along with tremendous amounts of data, including but not limited to original name, size, date of origin, manufacturer, and cryptographic hash values of the content. This database has over 52 million file references.

 

BIA identifies files as a KFF if the SHA-1 hash of the collected file matches any SHA-1 hash in the NSRL data set. In a random sample of nearly 60 million documents, BIA's KFF strategy has identified over 1 ¼ % of files as not relevant. BIA's capabilities in technology and resources that implement these technologies surpass many standard data management processing systems.