Question 1

What is eDiscovery Software?

Accepted Answer

eDiscovery software, or electronic discovery software, handles the discovery process for electronic information prior to civil or criminal legal proceedings. eDiscovery tools identify, collect, and produce electronically stored information (ESI) for use in a lawsuit or investigation. Common features of eDiscovery solutions include legal hold, early case assessment, document collection, document production, document processing, and document review. More robust solutions offer analytics and data visualization tools to help legal teams understand the data.  
 eDiscovery solutions search for and collect documents and data, quickly export and analyze information, share files with colleagues and clients, integrate with other software tools to streamline processes, and maintain the security of files and data. 
 The eDiscovery industry, including eDiscovery services, has exploded in the past couple of years. The increase in popularity is due to several reasons, with the two major ones being the improvement in the technology powering eDiscovery solutions and the increase in the number of documents housed digitally. eDiscovery solutions save law firms and legal departments time and money by streamlining legal teams’ workflow for ESI, which has expanded far beyond email to include dozens of types of admissible documents. The major use cases include criminal and civil litigation, internal investigations driven by regulatory oversight, public information requests, and data privacy maintenance (especially relevant given GDPR and the increased focus on privacy).  
 The technology relies on optical character recognition (OCR) and predictive coding, which refers to the application’s process of combing through a subset of documents for relevant information based on input from the user and making a determination as to what qualifies. The rise in predictive coding, which integrates artificial intelligence (AI) into the eDiscovery workflow, has improved the utility of eDiscovery applications and led to wider adoption. 
 There are several use cases for eDiscovery software, with the major ones being as follows: 
 Legal hold: eDiscovery can track and create auditable trails for users’ legal holds. 
 Early case assessment: The early stages of a case are crucial to shaping the future development of litigation proceedings. eDiscovery tools give the legal team the ability to organize, tag, and prioritize large swaths of unstructured data. 
 Discovery projects: eDiscovery solutions ensure that the discovery period is as painless as possible while maintaining document security and compliance. 
 Internal investigations: eDiscovery software can be used by legal teams in internal investigation cases to gather and digest as much information as possible without being obtrusive. Legal, compliance, and HR teams can all utilize the software to gather relevant documents that get to the heart of a dispute. 
 Third-party subpoenas: eDiscovery software can help businesses respond to government and third-party subpoenas quickly and easily. These solutions gather relevant documents and get them to the necessary parties. 
 Document production: These solutions create documents in various formats, organize relevant files, and create privilege logs so that document production is quick and easy for legal teams.

Question 2

What are the Common Features of eDiscovery Software?

Accepted Answer

The following are some core features within eDiscovery software that can help users: 
 Document collection: eDiscovery software collects documents from various data sources while producing an auditable trail. 
 Data processing: The software processes electronic documents and extracts relevant information via metadata combing, native application imaging, and domain parsing. The user feeds data to the engine, and the application processes it, preparing it for legal review.  
 Document review: eDiscovery software processes documents and extracts relevant information via metadata combing, native application imaging, and domain parsing. 
 Permissioned access: The solution Isolates and protects privileged or password-protected documents to allow only the access necessary.  
 Project analytics: It analyzes discovery projects and produces data visualizations based on available project information. These tools can help analyze discovery projects and produce data visualizations to help legal professionals get a better understanding of what the data says. 
 Legal hold: eDiscovery software automates the process of preserving ESI relevant to anticipated litigation.  
 Document production: Document production is a key feature of eDiscovery software. Legal professionals set up their application to trawl through and select relevant documents based on key indicators such as specific words or phrases. eDiscovery tools highlight the relevant ESI and get it ready for the legal process post discovery. 
 Assisted review: By leveraging the assisted review feature of an eDiscovery platform, legal professionals can improve the accuracy of document review and ensure that they’re not missing relevant information. 
 Case dynamics and transcripts: Some eDiscovery platforms provide users with tools that house case documents and create links between different legal documents. Transcripts can be linked to disparate case documents, and new information can be added and analyzed as the case develops. 
 Auto-detection of privileged materials: eDiscovery software typically combs through relevant ESI to identify and flag privileged documents so the team does not waste time on them. 
 Some eDiscovery solutions also include:  
 User reporting: The solution tracks and reports on reviewer activity for specific projects. 
 Project templates: The software provides templates for different project types. 
 Automated review: eDiscovery software leverages machine learning to automatically review and analyze documents under review. 
 Data visualization: Certain eDiscovery solutions contain data visualization tools, which help legal professionals grasp the information and story presented by specific data sets. 
 Real-time chain of custody: This feature refers to the auditable trail of digital fingerprints left on legal documents by the eDiscovery application.

Question 3

What are the Benefits of eDiscovery Software?

Accepted Answer

Streamline the discovery process: Legal professionals use eDiscovery software to streamline the discovery process. What was previously an arduous process, painstakingly combing through thousands of documents by hand, has now been vastly improved by the introduction of AI-powered eDiscovery software. The majority of law firms are moving litigation operations, specifically eDiscovery activities, in house. This shift means an increase in the amount of work for in-house legal teams and therefore an increase in the need for efficient processes and automation. 
 Cost and time savings: A major reason for using eDiscovery software is to save time and costs during the discovery process. These solutions allow law firms to save time by providing simultaneous keyword search in multiple locations, automatic deduplication of search results, permission-based filtering of search results, indexing, retrieval of unindexed items, automated redaction, and archiving of documents. As the amount of ESI has skyrocketed, discovery costs responded accordingly. AI-powered eDiscovery solutions have helped to keep costs down while improving accuracy and data collection efficiency. 
 eDiscovery software implementation saves legal teams time and allows them to cut down on costs associated with document review, early case assessment, and all discovery-related tasks. The myth that manual, human document review is more accurate than computer-assisted review seems to have died out, as mounds of empirical evidence supporting the incredible accuracy of eDiscovery solutions in identifying relevant documents has eliminated the support of reasonable observers. Multiple studies have been completed comparing human document review accuracy and automated document review, and the automated systems easily outpaced the human-generated numbers.

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