Best eDiscovery Solutions

The technologies and processes surrounding e-discovery can be complex because so much data is involved. Electronic documents are also much more dynamic than hard copy documents and can include metadata such as author and recipient information, time and date stamps, and file properties. The original content and metadata must be preserved so that later in the litigation process no one can claim that the evidence was tampered with or otherwise spoiled.

After both parties identify all data, any (electronic and/or hard-copy) documents that are potentially relevant will be placed under legal hold. This means the documents cannot be deleted or modified in any way. Data are then collected and extracted by the eDiscovery software, which integrates with file storage, database, and backup systems and other case management tools.

After the data are indexed in a database, they are then analyzed in order to cull whatever is not deemed relevant. The data that are extracted for use in the case are hosted in a secure environment where they are coded (often paralegals or contract attorneys) based on relevance.

Sometimes the relevant documents are converted into TIFFs or PDFs so that privileged or irrelevant information can be redacted. Predictive coding, CAR (computer-assisted review), TAR (technology-assisted review), and other analytic software helps to reduce the number of documents that the attorneys need to review, as well as to prioritize the documents they do review. This cuts hours spent on the case and therefore the cost of attorney fees.

Many law firms continue to use outmoded methods, such as paying paralegals an hourly fee review case-related ESI manually. This approach is long, cumbersome, and can often result in errors. E-discovery software improves and expedites the entire e-discovery process by identifying relevant documents more accurately and more efficiently and therefore making the legal proceedings less costly.

Benefits of eDiscovery software include:

1. Improved discovery efficiency
2. Increased accuracy of identification of relevant documents.
3. Reduction of discovery-related costs
4. Leveraging of document tools for collaboration

Features to look for in an e-Discovery solution include:

1. Recursive data parsing - Ability to read documents in their original formats (TIFF, PDF, etc. ) and extract content and metadata from all files, including those that are nested within subdirectories, contained within other files, password-protected, or even corrupted or infected. If the parser encounters a file that it can’t handle, it must notify the user so that they can take action.
   
   
2. Search index and interface - The data provided should be clean, normalized, and structured so that it can be used to create a search index. Look for the possibility of Boolean (“and”/”or”/”not”), “fuzzy,” “stemming,” and “proximity” searches, which will maximize your searching capabilities. “Fielded” searches - those that search by sent date, email address, etc, are also very useful.
   
   
3. Organization/annotation/tagging of documents - As documents are reviewed, they go through many different hands. It is useful for attorneys to be able to label documents that are privileged, that relate to a particular topic, etc. This way they can easily be pulled out as needed.
   
   
4. Audio transcription - A search feature can only search documents for text. If a term is mentioned in a video or audio recording, it will not come up in a search. Some e-Discovery applications can create a transcript of audio and video files so that that text can be searched as well. If it does not have the ability to transcribe video and audio, it should at least flag the file as lacking text so that it can be reviewed manually.
   
   
5. Optical Character Recognition - As audio and video files need to be transcribed into text, so do images and screenshots. OCR is used to locate text and make it visible to the search index.
   
   
6. Email threading - Emails can be crucial to a case. The review tool should be able to group emails with their attachments and with any replies in the email “chain.”
   
   
7. Machine learning - Also known as “Technology Assisted Review or “Predictive Coding,” this technology can be faster and more accurate than keyword searching and is recommended when working on cases with large data sets.
   
   
8. Data visualization - An e-Discovery program should be able to create various graphs and diagrams to help the legal team visualize how the information collected comes together. This might include pie graphs showing the frequency of various file types, timelines showing the volume of email traffic between specific people involved in the case, etc. Not all visualization is necessarily helpful so it is important to have an idea of what kind of information you will be looking for before choosing an e-Discovery tool.
   
   
9. Document conversion - When litigators are ready to share their files, they will have to merge multiple documents and often convert them into different file formats. This is a burdensome part of the process, which can be eased by a good e-Discovery tool.