This GigaOm Research Reprint Expires: Sep 24, 2023

GigaOm Radar for E-Discoveryv1.0

1. Summary

Organizations can face litigation or discovery requests at any time due to legislation or regulations such as the general data protection regulation (GDPR). Searching for a particular item among millions of documents, emails, and other content is like looking for the proverbial needle in a haystack. Without the right tools in place, it is extremely time-consuming and costly, and many enterprises might choose to accept a fine and the associated brand damage rather than attempt to locate the required content. In some countries, however, failure to produce documents and records could result in summary judgment against them.

E-discovery software makes finding that single piece of content possible via the e-discovery process. This process is based on the electronic discovery reference model (EDRM), a framework that defines all of the stages of e-discovery, from identifying the data to presenting it to a court. Solutions can cover the entire process, from the initial searches and putting legal holds on data that may be relevant, to the final presentation of the content to a court or opposing counsel. And the software has additional benefits, such as the ability to run risk assessments on the content to ensure there are no smoking guns that could be the subject of litigation in the future.

E-discovery software manages the process of proactively discovering, preserving, collecting, processing, reviewing, producing, and presenting electronically stored information (ESI). Platforms follow the EDRM, with some providing end-to-end capabilities, while others stick to either the left-hand side (identification, preservation, collection, and processing) or the right-hand side of the model (review, analysis, production, and presentation).

There are two distinct audiences for e-discovery software: enterprises that typically undertake the initial searches for content that may be relevant to a matter; and legal departments within large enterprises or legal firms responsible for reviewing and putting together the final set of content.

When implementing e-discovery software, enterprises should be proactive so they’re ready to act as soon as a request is received. Discovery must be undertaken in a timely fashion, and therefore procuring a solution must occur well before its need becomes critical, when there is time to properly assess its capabilities to ensure that it meets the enterprise’s requirements. The ability to undertake an early case assessment (ECA) will allow counsel and courts to determine whether a matter is worth pursuing or if a settlement should be sought.

This GigaOm Radar report highlights key e-discovery vendors and identifies vendors and products that excel. In the corresponding GigaOm report “Key Criteria for Evaluating E-Discovery Solutions,” we describe in more detail the key features and metrics used to evaluate these vendors. Together, these reports provide an overview of the category and its underlying technology, identify leading e-discovery offerings, and help decision-makers evaluate these platforms and make a more informed investment decision.

How to Read this Report

This GigaOm report is one of a series of documents that helps IT organizations assess competing solutions in the context of well-defined features and criteria. For a fuller understanding, consider reviewing the following reports:

Key Criteria report: A detailed market sector analysis that assesses the impact that key product features and criteria have on top-line solution characteristics—such as scalability, performance, and TCO—that drive purchase decisions.

GigaOm Radar report: A forward-looking analysis that plots the relative value and progression of vendor solutions along multiple axes based on strategy and execution. The Radar report includes a breakdown of each vendor’s offering in the sector.

Solution Profile: An in-depth vendor analysis that builds on the framework developed in the Key Criteria and Radar reports to assess a company’s engagement within a technology sector. This analysis includes forward-looking guidance around both strategy and product.

2. Market Categories and Deployment Types

To better understand the market and vendor positioning (Table 1), we assess how well e-discovery solutions are positioned to serve specific market segments.

  • Small-to-medium business (SMB): In this category, we assess solutions on their ability to meet the needs of organizations ranging from small businesses to medium-sized companies. Also assessed are departmental use cases in large enterprises, where ease of use and deployment are more important than extensive management functionality and feature set. Note that while the initial search, collection, and production stages of the e-discovery process may be undertaken in-house, it is likely that the review, analysis, and presentation will be outsourced to a legal firm.
  • Large enterprise: Here, offerings are assessed on their ability to support large projects, which will likely be more complex than those in SMBs, with much larger data volumes involved. Scalability is a big differentiator, as is the ability to deploy the same service in different environments. In terms of e-discovery, large enterprises are more likely to have substantial legal departments and have counsel working on matters full-time, and, therefore, be in a position to handle the entire discovery process.
  • Law firms: These are large companies that are often global or at least multinational, with expertise in the e-discovery space and undertake review and analysis on behalf of clients, often from the SME space.

In addition, we recognize three deployment models for solutions in this report: cloud service provider (CSP), on-premises, or hybrid.

  • CSP: Provides a solution available only in the cloud. Often designed, deployed, and managed by the vendor who supplies the software, they are available only from that specific provider. The big advantage of this type of solution is the integration with other services offered by the CSP (functions, for example) and its simplicity.
  • On-premises: The solution is provided as software only for deployment in the customer’s own data center. The customer owns all the hardware and builds its own infrastructure. Modern software is often cloud-first or cloud-native, making it easier to migrate to the cloud in the future.
  • Hybrid: These solutions are meant to be installed both on-premises and in the cloud, allowing them to build hybrid or multicloud storage infrastructures. The integration with the single cloud provider could be limited compared to the other option and more complex to deploy and manage. On the other hand, they are more flexible, and the user usually has more control over the entire stack regarding resource allocation and tuning.

Table 1. Vendor Positioning

Market Segment

Deployment Mode

SMB Large Enterprise Law Firms CSP On-Premises Hybrid
CloudNine
Consillio
Digital WarRoom
DISCO
Everlaw
Exterro
IBM
IPRO
Knovos
Logikcull
Microsoft
NextPoint
Nuix
Onna
Opentext
Proofpoint
Relativity
Veritas
Zapproved
3 Exceptional: Outstanding focus and execution
2 Capable: Good but with room for improvement
2 Limited: Lacking in execution and use cases
2 Not applicable or absent

3. Key Criteria Comparison

Building on the findings from the GigaOm report, “Key Criteria for Evaluating E-Discovery Solutions,” Table 2 summarizes how each vendor included in this research performs in the areas that we consider differentiating and critical in this sector. Table 3 follows this summary with insight into each product’s evaluation metrics—the top-line characteristics that define the impact each will have on the organization.

The objective is to give the reader a snapshot of the technical capabilities of available solutions, define the perimeter of the market landscape, and gauge the potential impact on the business.

Table 2. Key Criteria Comparison

Key Criteria

Recursive Data Parsing Real-Time Tracking of E-Discovery Process Tagging & Organizing Documents Search Data Governance Data Presentation Predictive Coding
CloudNine 2 2 3 3 3 1 1
Consillio 2 2 2 3 2 1 2
Digital WarRoom 2 2 2 3 2 1 2
DISCO 3 2 3 3 2 1 2
Everlaw 3 2 3 3 2 3 3
Exterro 2 3 2 3 3 1 2
IBM 3 3 2 3 2 0 0
IPRO 2 2 2 3 2 3 1
Knovos 3 3 2 3 3 2 2
Logikcull 1 3 3 3 2 1 0
Microsoft 3 2 2 3 2 1 2
NextPoint 2 2 3 3 2 2 0
Nuix 2 2 3 3 3 1 3
Onna 3 2 3 2 2 0 0
Opentext 3 3 3 3 3 1 3
Proofpoint 0 2 2 2 3 1 2
Relativity 3 2 3 3 3 1 3
Veritas 3 3 3 3 3 1 2
Zapproved 3 2 2 3 2 1 0
3 Exceptional: Outstanding focus and execution
2 Capable: Good but with room for improvement
2 Limited: Lacking in execution and use cases
2 Not applicable or absent

Table 3. Evaluation Metrics Comparison

Evaluation Metrics

Speed Flexibility Scalability Support Ease of Use
CloudNine 2 2 2 2 1
Consillio 2 3 3 3 2
Digital WarRoom 2 2 2 2 1
DISCO 3 3 3 3 3
Everlaw 2 3 2 3 3
Exterro 3 3 3 3 3
IBM 2 2 2 2 2
IPRO 2 2 3 2 2
Knovos 2 3 2 3 3
Logikcull 2 2 2 3 3
Microsoft 2 2 2 2 2
NextPoint 2 3 2 2 2
Nuix 2 3 2 2 3
Onna 2 3 2 2 3
Opentext 2 3 3 3 3
Proofpoint 2 2 2 2 2
Relativity 3 2 2 3 3
Veritas 2 3 2 2 3
Zapproved 2 3 2 3 3
3 Exceptional: Outstanding focus and execution
2 Capable: Good but with room for improvement
2 Limited: Lacking in execution and use cases
2 Not applicable or absent

By combining the information provided in the tables above, the reader can develop a clear understanding of the technical solutions available in the market.

4. GigaOm Radar

This report synthesizes the analysis of key criteria and their impact on evaluation metrics to inform the GigaOm Radar graphic in Figure 1. The resulting chart is a forward-looking perspective on all the vendors in this report, based on their products’ technical capabilities and feature sets.

The GigaOm Radar plots vendor solutions across a series of concentric rings, with those set closer to the center judged to be of higher overall value. The chart characterizes each vendor on two axes—balancing Maturity versus Innovation, and Feature Play versus Platform Play—while providing an arrow that projects each solution’s evolution over the coming 12 to 18 months.

Figure 1. GigaOm Radar for E-Discovery

As you can see in the Radar chart in Figure 1, coverage varies significantly in this market. Vendors are positioned along the Feature Play and Platform-Play axis based on whether they focus on the left or right side of the EDRM model (Feature Play) or whether they provide end-to-end EDRM capabilities (Platform Play).

IBM and Onna focus on the left-hand-side of the EDRM; Consillio, Digital WarRoom, Knovos, and Logikcull address the right-hand side of the model; and CloudNine, DISCO, Everlaw, Exterro, IPRO, Microsoft, Nextpoint, Nuix, OpenText, Proofpoint, Relativity, Veritas, and Zapproved provide end-to-end EDRM capabilities.

IBM and Microsoft are Challengers. Microsoft is gradually adding features and new functionality to expand its platform, and its arrow, therefore, points toward the center of the Radar. For IBM, in contrast, e-discovery is not a priority; its arrow is pointing sideways, away from the center, reflecting that IBM has a large solution and partner ecosystem but that it’s not currently expanding its e-discovery capabilities.

OpenText and Veritas are Leaders. They’re still aggressive despite being well-established e-discovery vendors, and they are both Fast Movers, moving toward maturity and advancing to the center of the Radar. However, Veritas intends to expand its capabilities, whereas OpenText is just enhancing and adding to existing capabilities.

Nuix and Everlaw are Leaders in the Innovation half, but are moving toward maturity as they enhance their capabilities. Nuix is a Fast Mover and Everlaw an Outperformer. Exterro and Knovos are also Leaders and in the Maturity half of the Radar, moving toward the center. Exterro is a Fast Mover and Knovos is an Outperformer.

Digital WarRoom, Logikcull, Nextpoint, Proofpoint, and Relativity are all Challengers in the Maturity half and moving toward the center of the Radar. However, due to its strength across the key criteria, Relativity is the one most likely to become a Leader first—if it adds emerging technologies to its portfolio.

IPRO and DISCO are also Mature Challengers. IPRO is a Fast Mover as it’s adding features relatively quickly with more frequent updates than many vendors. By contrast, DISCO is an Outperformer as it’s adding features at an even faster pace. Both vendors are closing in on the Leaders circle.

CloudNine, Consillio, Onna, and Zapproved are Innovative Challengers. Onna and Zapproved are Fast Movers as they’re addressing shortfalls in their portfolios. Consillio is a Forward Mover as its main focus is consulting, and CloudNine is an Outperformer due to its recent acquisitions.

Inside the GigaOm Radar

The GigaOm Radar weighs each vendor’s execution, roadmap, and ability to innovate to plot solutions along two axes, each set as opposing pairs. On the Y axis, Maturity recognizes solution stability, strength of ecosystem, and a conservative stance, while Innovation highlights technical innovation and a more aggressive approach. On the X axis, Feature Play connotes a narrow focus on niche or cutting-edge functionality, while Platform Play displays a broader platform focus and commitment to a comprehensive feature set.

The closer to center a solution sits, the better its execution and value, with top performers occupying the inner Leaders circle. The centermost circle is almost always empty, reserved for highly mature and consolidated markets that lack space for further innovation.

The GigaOm Radar offers a forward-looking assessment, plotting the current and projected position of each solution over a 12- to 18-month window. Arrows indicate travel based on strategy and pace of innovation, with vendors designated as Forward Movers, Fast Movers, or Outperformers based on their rate of progression.

Note that the Radar excludes vendor market share as a metric. The focus is on forward-looking analysis that emphasizes the value of innovation and differentiation over incumbent market position.

5. Vendor Insights

CloudNine ESI Analyst and CloudNine Review

CloudNine is headquartered in Houston, Texas. It expanded its e-discovery portfolio by acquiring LexisNexis Concordance, targeting large enterprises, SMBs, and the public sector.

CloudNine’s e-discovery solutions are CloudNine Review and CloudNine ESI Analyst; they’re SaaS-based, easy to use, and can be used individually or in combination. Together with its other products, these tools create an investigation platform that handles both traditional and modern data types and provides continuous process improvement and personalized workflows. The full portfolio includes LAW, Concordance, CloudNine Collection Manager, Data Wrangler, Discovery Portal, and Explore, with each component available individually or as a comprehensive and integrated solution, either hosted or on-premises.

CloudNine provides self-service review with automated processing and production, text message deduplication, threading, actor normalization, near-native productions, tag-based redactions, near-duplicate identification, and language detection. It can display data at an item or thread level; supported data types include text messages, chats, geolocation, computer activity, transactions, and social media, and it supports more than 4,500 file types.

CloudNine supports several search methods, including Boolean, proximity, fuzzy word, stemming, phonic, and regex. Simple searches can be created using just a single field, while more complex searches can be built with multiple layers, even if users have no search syntax expertise, by using the search builder. Text and chat-based searching involves creating two indexes on a single message across a 24-hour thread.

CloudNine Review includes self-service loading, review, and production. Individual users can be assigned to each matter with different levels of access. Administrators can use CloudNine’s Discovery Queue to track actions across all matters. Review sets can be created to track document review speed, tagging percentage, total documents reviewed, and time spent. CloudNine ESI Analyst supports redaction with the ability to withhold or redact specific messages.

CloudNine includes a legal hold capability, which creates a notification that tracks when the hold is sent, when it is accepted, and when any reminders have been sent.

Admins can create unlimited custom tags and fielded data. These can include simple “yes/no” or complex nested tags and allow single or multiple selections within the tags. Admins can also create groups, manage fields, and set access rights across different users.

Strengths: CloudNine scored well in the tagging and organizing documents, search, and data governance key criteria. It allows content to be managed and culled, reducing the volume of content to be manually reviewed. It is also extremely strong in its support for social media content, enabling enterprises to import content from new sources.

Challenges: CloudNine’s review capabilities don’t include predictive coding. This is a feature deployed by many vendors to massively reduce the amount of manual review that has to be undertaken. And it doesn’t take advantage of AI, which has to be regarded as a weakness as AI is increasingly used in e-discovery products to help automate tasks. However, CloudNine is looking to invest in technology-assisted review (TAR).

Consillio Sightline

Consillio was founded in 2002 as First Advantage Litigation Consulting, a provider of forensics consulting services to multinational corporate clients. Following the acquisition of True Data Partners, Consillio expanded into data processing and e-discovery services, and in late 2005, it launched its web-based review technology, Global RPM and Secure Data Hosting services. The company rebranded itself as Consillio in 2013. Through acquisitions and mergers, its software capabilities have increased, as has its global reach.

Consulting is a huge part of Consillio’s e-discovery business, but it does offer software, including Sightline, a review platform. Target markets for Sightline are large law firms, enterprises, and government entities.

Consillio offers a flexible cloud-based model that allows enterprises to run the whole process themselves, from configuring the capabilities, uploading their own searches, managing their users, and running their reports, or they can take advantage of Consillio’s project managers. Some features, such as predictive coding, are available only through Consillio’s consulting services.

Consillio Sightline comprises ECA, analytics, and review, enabling users to investigate, analyze, review, and produce documents. It was designed to simplify the review process and offers a number of features to do so. It provides optimized document sorting so that similar documents are grouped together. Text, audio, and video can all be redacted. Coding forms are available, which promote a logical flow, and personalized one-click tools are available, including coding stamps. Additionally, entire families of documents, email threads, or textual near-duplicate groups can be coded as a unit. Conceptual analysis allows the identification of documents that are conceptually relevant to the material investigators seek.

AI models—including IP theft, PII/PHI/PCI, discrimination/harassment, and fraud/FCPA—are customizable and reusable and can be used to identify actionable facts. These models can be used across multiple matters through available project templating.

Matters that are similar in terms of workflow patterns can use an existing project as a template, which means that existing security groups, tags, coding forms, production templates, assignments, users, saved searches, and other elements do not need to be created anew.

Visualizations are provided through the reporting capability, including personalized dashboards and customized self-service reports that show a wide range of metrics, such as review progress, top reviewers, reviewers with most documents to review, and batch progress. Also available are thread maps.

Strengths: Consillio has outstanding search capabilities, which is not surprising given that the platform is focused on making the review process easier by culling non-responsive data using advanced search capabilities and AI. It also has excellent video support capabilities and can redact video, including faces, an important feature as, when presenting video evidence, faces not relevant to the matter should not be displayed.

Challenges: Consillio does not provide predictive coding in its software solution, which means that documents have to be reviewed manually. Predictive coding is available through Consillio’s consulting services.

Digital WarRoom eDiscovery

Headquartered in Seattle, Washington, Digital WarRoom provides e-discovery solutions that can be deployed on-premises or in the cloud, with hosted and private cloud options available. It has several pricing models for single and multiple matters, as well as a desktop version for single users or small firms, providing a great deal of flexibility. The solution is suited to SMBs, large enterprises, and law firms.

Digital WarRoom eDiscovery starts by ingesting collections into the solution, achieved through drag-and-drop. All metadata is extracted from the files to enable filtering. The tool indexes every word in the documents, making them searchable during the review process. Multiple filters can be applied with one or more keywords during the search process to filter down the subset of documents, eliminating non-relevant data.

Documents can be marked up easily with marks, issue codes, and protective order designations using a customizable marking palette. Several marking workflows are provided to suit different requirements. Each time a document is marked as privileged, a new privilege log entry is automatically added. The log records which reviewer ID marked the document and when the document was marked.

Redactions are supported with the ability to redact any element of a document and add a custom label. The redaction tool draws boxes on TIFF images.

A heat map grid showing “Who to Whom” displays emails that meet the search criteria with individual email senders on the y-axis and all email recipients on the x-axis. They are colored red (which shows the most common email correspondence) and orange (showing less common correspondence).

Email threads can get very complicated with multiple CCs and BCCs on different emails in the thread. The email thread visualizer addresses this by allowing users to visually track long threads across multiple users.

The OCR engine detects and indexes words from images and PDFs. All words in images are scanned, ensuring they become searchable during document review. Content can also be deduplicated, and any designations assigned to a document are propagated across all duplicated documents.

Users can create production sets by first creating images that have confidentiality designations and Bates numbering applied. Metadata can be overlaid from other productions, allowing metadata fields from other platforms to be aligned with those within Digital WarRoom. The production sets can be exported in a number of formats.

Strengths: Digital WarRoom has excellent search capabilities, allowing content to be culled to reduce the amount that needs to be reviewed. Its flexible deployment options range from on-premises and private cloud for large enterprises that don’t want to trust their data to a public cloud to a desktop version for small firms that want to control their own discovery process. Its pricing for single or multiple matters can suit all budgets and requirements.

Challenges: Digital WarRoom lacks collection capabilities, which prevents it from being an end-to-end solution. This will not be a problem for many enterprises, because e-discovery is typically handled by two distinct sets of users. However, enterprises handling the entire e-discovery process in-house may prefer to buy a single end-to-end tool.

DISCO Ediscovery

DISCO Ediscovery is a cloud-based e-discovery solution that provides end-to-end capabilities, including matter creation, which comprises adding users and assigning permissions, processing data, analytics, review, production, and creation of exhibit sets. Target markets are SMBs, large enterprises, the public sector, and law firms. The product was designed to be used by attorneys, paralegals, project managers, data specialists, forensic specialists, review managers within law firms, corporate legal departments, and service providers.

DISCO Ediscovery is a single integrated solution hosted on Amazon Web Services (AWS) that features ECA, with the ability to easily move documents from ECA to active review. DISCO also offers a legal hold application (DISCO Hold) and a collaborative deposition management application (Case Builder). In addition, DISCO Request automates legal request compliance, and there’s a full suite of productized professional services that includes forensic identification and preservation, collection, and data remediation.

Data can be ingested into DISCO Ediscovery in multiple ways, including drag-and-drop into the web application. Once ingested, data can be deduplicated on a global basis or at the custodian level, and settings can be applied that define how the data is presented. Various processing options are supported, including extraction of containers, attachments, metadata, and text; filtering for NIST and common system file types; deduplication; creation of near natives; import/export of PDFs and HTML; rendering of spreadsheets; imaging; similar-document detection; email threading; and calculation of AI scores. Metadata and text—including hidden content—are made available for analysis, search, and production.

The solution is highly scalable and supports the simultaneous review of documents by large teams. Just-in-time batching identifies documents for a batch only when a reviewer is ready to check the batch out. This allows each batch to take advantage of the constantly updated AI model for prioritization.

Real-time dashboards are provided for review metrics, which offer insights into review progress and projected completion, as well as monitoring review tagging behavior to identify outliers among reviewers. Custom reports can be created by exporting the metrics.

Tags can be organized into contextual tag groups, such as the “Privilege” tag group, which might include tags such as Work Product and Attorney-Client. DISCO provides common tags, but users can create their own to support multilevel, complex review protocols. Conditional coding rules can also be applied. AI tag predictions are supported in which predictive scores are provided by tag category for all documents in a database. This feature can be used to create a prioritized review. The solution includes extensive search capabilities, and TAR is available using DISCO’s AI capabilities. AI is also used in its predictive coding capabilities with the ability to build ML models to automate much of the review process.

DISCO Hold preserves data in place, and it currently integrates with solutions such as Workday, Okta, and SuccessFactors. DISCO plans to extend these capabilities into the Ediscovery product to improve ease of use for legal and IT administrators.

Strengths: DISCO scored well on recursive data parsing, tagging, document organization, and search, and its predictive coding capabilities allow legal teams to speed up the review process, making it suitable for enterprises and law firms with multiple matters or very large review sets. AI is embedded across the solution, as is support for social media sources and video.

Challenges: DISCO currently lacks cloud connectors to directly collect data from cloud-based enterprise applications, like Microsoft 365 and Google Workplace, but this is on its roadmap.

Everlaw Platform

Headquartered in Oakland, California, Everlaw was founded in 2010 by AJ Shankar, a computer scientist, and Jeff Friedman, a practicing lawyer. Its target markets are law firms, corporations, and state, local, and federal governments. It is a cloud-native solution that incorporates uploads, legal holds, search, review, productions, analytics, and predictive coding. Everlaw’s strength is on the right-hand side of the EDRM but it offers a full end-to-end product. Its cloud connector framework enables direct connections to a number of sources, including Slack, Box, Dropbox, Google Drive, SharePoint, OneDrive, and Google Vault. For other files, users can drag and drop files into Everlaw, or Everlaw’s data operations team can assist with more complex data types. Everlaw provides an ECA environment that allows documents to be processed and imaged prior to being promoted to active review. ECA features include robust concept clustering, search capability, single-click immediate promotion, and a data visualizer.

Legal holds can be applied to data, and an unlimited number of holds can be created and deployed to multiple custodians, with a simple process for modifying and editing holds. Automated tracking and escalations are supported with automated notifications applied.

Extensive search capabilities are available with visually built search queries, stackable metadata, and work-product filters. Everlaw Smart Terms can search emails automatically, and find communications between specific people rather than email addresses.

Everlaw’s real power is its considerable review capabilities, which include predictive coding using a continuous, adaptive ML system. Users assign custom ratings, codes, and attributes, and the algorithm learns to predict document relevance. They can also apply weightings to the most relevant words or phrases to improve the accuracy of the results.

Other review features include the automatic translation of 109 languages, the ability to apply coding rules, and an assignments tool to organize the allocation of review documents across teams. Automatic redaction of words, phrases, metadata, entire pages, or patterns is also provided, with customizable redaction stamps that state the reason for the redaction—such as personal identifiable information (PII). Audio and video transcription is supported with an automatically generated transcript, synced during playback and searchable.

Analytics features include visualization of clustering to identify conceptually similar documents; data visualization showing metrics, including document dates, metadata, contents, formats, review activity, predicted relevance; and email threading.

Strengths: Everlaw is particularly strong in its review capabilities, using predictive coding to automate the review process and reducing manual review. It also scored well in recursive data parsing, the real-time tracking of e-discovery processes, and tagging and organizing documents, providing valuable tools for review teams. Everlaw is also outstanding in its support for video and audio, particularly for transcription, as the transcribed content can be indexed and searched. Unlike many of its competitors, Everlaw includes presentation capabilities, allowing users to prepare content for trials and deposition.

Challenges: Although Everlaw provides end-to-end capabilities, its real strength lies in the right-hand side of the EDRM, which may deter some enterprises from using it for end-to-end capabilities. Everlaw needs to emphasize its end-to-end capabilities as many companies that use their own internal legal teams to undertake e-discovery may not be aware that they could use Everlaw for the entire process.

Exterro Orchestrated E-Discovery

Exterro was founded in 2008, and is headquartered in Beaverton, Oregon, US, with global offices in Germany, India, and the UK. The company was built with the idea that e-discovery is a business process, and is subject to measurement, management, and optimization. The company has grown both organically and through acquisition, and its Exterro Orchestrated E-Discovery suite is a comprehensive legal governance, risk, and compliance (GRC) software platform.

Deployment options are SaaS, private cloud, and software only. Target markets are the public sector, law enforcement, law firms, enterprises, and service providers.

Exterro offers extensive capabilities across the board—in legal hold, in-place preservation, comprehensive interview, e-discovery data management, ECA, collection and processing, review, smart labeling, production, and legal project management.

The Legal Hold product manages the entire preservation process including custodian scoping, creation and distribution, reminder, escalations for legal hold obligations, and acknowledgment. The In Place Preservation solution complements the Legal Hold product by integrating with enterprise data sources and preserving potentially responsive data in place, thus preventing spoliation without having to collect data. Features include an employee change monitor that detects changes to data stored in an HR system and automatically acts, such as sending alerts to key stakeholders when an employee leaves. The integration with HR systems also provides historical custodial views, so former custodians can be put on hold. Integration with Microsoft 365 allows the software to identify key data and custodian relationships from data stored in Microsoft 365 without it having to be scanned or indexed. Communication patterns can be highlighted and multiple searches built to collect the required data.

A dashboard shows information holds, responses, and compliance by matter, department, manager, and custodian. Recommendations to improve compliance are made using ML.

Exterro supports ECA with analytics and predictive intelligence capabilities to help identify the most important documents in a dataset prior to collection. AI enables visualizations for identifying contextual relationships between custodians and documents. This means that targeted collections can be initiated with the documents forwarded to review with a single click. More than 50 on-premises and cloud-based data sources are supported.

Exterro’s review capabilities include single-instance storage to ensure that documents are only collected, processed, and stored once, but they can still be used across multiple matters. The entire review process can be automated with the process configured for each review project according to the requirements of each stakeholder, which could be an in-house legal department, government agency, legal service provider, or law firm.

AI is embedded throughout review to provide document summaries, automated translation, and smart labeling algorithms to guide users to the documents most relevant to their assigned task. TAR is also provided to automate much of the review process.

Exterro Review can be used as a standalone document review solution, or as part of the Exterro Orchestrated E-Discovery suite. Use cases include privacy management, internal investigations, and FOIA public records requests.

Strengths: Exterro scored well in many areas. It has real-time tracking of the e-discovery process, search, and data governance, supporting the end-to-end management of complex e-discovery matters. It also has extensive AI capabilities throughout the platform, helping to automate e-discovery processes. Exterro offers a single orchestrated platform, which means that documents can be automatically passed between the different stages of the e-discovery process.

Challenges: Exterro does not include presentation capabilities, which means the final document set needs to be exported to a specialist presentation solution. This prevents Exterro from providing a truly end-to-end solution.

IBM eDiscovery Manager, IBM eDiscovery Analyzer

IBM is unusual in that it is one of the very few that focus only on the left-hand side of the EDRM. Its capabilities allow enterprises to search, cull, hold, and export case-relevant content to a review platform. However, IBM also provides information governance capabilities through its content management products, FileNet and Content Manager. Its e-discovery portfolio comprises IBM eDiscovery Manager and IBM eDiscovery Analyzer.

IBM eDiscovery Manager allows users to search ESI content, including documents and email, across multiple repositories and data types, with the ability to create cases to preserve potentially relevant ESI and manage it in place. It uses a web client and supports complex searches using various content properties individually or in combination. Full-text search of document content is also supported. An HTML viewer is included so that documents can be previewed for relevance if the native application is not available. Non-relevant ESI can be culled, reducing the reviewer workload further along the process. In addition, a full audit trail is provided of case activities to prove authenticity and chain of custody. The result set is produced in native, HTML, XML, or other formats for review in third-party review platforms.

Folders can be created to store search results for a matter, and a legal hold is applied to the documents as they are placed in a folder. Search terms associated with search results can be saved for future reuse. Searches can also be scheduled to be repeated at predefined intervals so that new documents can be found. Once the document set is complete, it can be exported for review.

IBM eDiscovery Analyzer is a browser-based application targeted at paralegals and attorneys, allowing them to search, view, and analyze archived documents. It uses sets of documents that have been identified as potentially relevant by eDiscovery Manager. As you’d expect with IBM, AI is embedded throughout the product. It helps users gain insights, supporting ECA by allowing users to identify key concepts and phrases, understand related facts and communication threads, locate critical pieces of evidence, and identify witnesses. This enables users to estimate the cost and risks of disclosing content, reduce review costs through its ability to refine case content, and cull non-relevant content.

Deployment options are on-premises with no cloud option provided.

Strengths: IBM scored well on recursive data parsing, tracking of processes in real time, search, and for its ability to collect and process content from multiple sources, including social media and other internet content. AI is used throughout the solution to enhance the content search, analysis, and visualization.

Challenges: A limitation is that IBM’s solution does not provide any capabilities on the right-hand side of the EDRM. With Watson Analytics, IBM is well able to create a review module with predictive coding to provide more of an end-to-end solution but has yet to do so, leading to a perception that e-discovery is not a big priority for IBM.

IPRO eDiscovery

IPRO Tech was founded as a litigation services provider in 1989, with its first solutions used for paper-based discovery. In 2004, it developed its first electronic discovery tool, eScan-IT. The acquisition of InData in 2017 added trial expertise and technology, and Montréal- and Frankfurt-based NetGovern provided specialism in agile information governance. Its most significant acquisition was Amsterdam-based ZyLAB, which added e-discovery and SaaS-based legal hold capabilities. The company is headquartered in Tempe, Arizona, US, with international offices in Canada, Germany, and the Netherlands. IPRO targets large enterprises, law firms, governments, the public sector, and legal service providers. The solution is available as SaaS or can be deployed on-premises, in public or private clouds, or as a hybrid implementation.

Capabilities include information governance, legal hold and preservation, internal investigations, data collection, ECA, document review, witness and trial preparation, and evidence presentation.

The legal hold feature provides a centralized system that allows users to issue legal holds to custodians and preserve all information across data sources. The system tracks all notifications, responses, and actions, and also produces court-ready reports. Workflow and automation capabilities allow legal holds to be drafted, issued, and lifted. Custodians can be automatically reminded of their holds, and escalations can be initiated when required. Data from on-premises and cloud systems can be preserved in place or held in archive.

The collection capability, part of a broader set called LiveEDA, allows data to be identified upfront, so only data that is likely to be responsive is collected. Users can search and see live data in-place, based on the relevant information that has been identified, with the ability to strategically negotiate the volume scope before data is collected. Data is indexed prior to collection and is continuously crawled. Visualizations allow users to identify relevant custodians and, by following their actions, locate other custodians, understand trends and patterns to see relationships, and uncover additional organizations or domains.

The Review module provides a workspace with a number of features that enable documents to be reviewed. According to IPRO, no prior knowledge is required to start reviewing documents. Review has built-in AI, allowing automated workflows to be built, including validation checks and advanced predictive coding. Review capabilities include creating, running, and saving searches; reviewing a document’s images; extracting text; viewing production history; tagging documents; and applying annotations and redactions to documents.

Strengths: IPRO has outstanding search capabilities, which is important because it uses search to cull documents to reduce the volume of documents for manual review. The solution is also one of only a few in this space that provide presentation capabilities, so enterprises do not need to implement a separate product for this task.

Challenges: IPRO has two review solutions, one focused on corporate and government legal teams and the other for law firms and service providers. This may confuse buyers as to which solution is best for them.

Knovos nayaEdge, eZManage, eZReview

Knovos was founded in 2002, and is headquartered in Fairfax, Virginia, with offices throughout the US, EU, and Asia. More than half of Knovos’ staff is dedicated to R&D and engineering, with a heavy focus on developing technology and solutions. Its e-discovery EDRM Lifecycle Management solution encompasses data governance, matter management, and e-discovery management. Target markets are SMBs, large enterprises, the public sector, and law firms. Deployment options are on-premises, SaaS, or on a public or private cloud.

NayaEdge provides information governance, compliance monitoring, and a smart risk repository system. eZManage is a case management and legal hold system, and eZReview is an end-to-end e-discovery solution.

eZReview capabilities include data processing, ECA, analysis, review, and production. A dashboard provides monitoring and process oversight, and security features protect confidential, classified, and other sensitive data. Use cases include investigations, subpoena responses, discovery requests, knowledge repositories, and FOIA responses. The Knovos built-in analytics engine uses multidimensional analysis to provide a 360-degree view of the data.

Support is provided for more than 350 file formats with the ability to gather content from zip files, mailboxes, archives, and forensic image containers. Knovos plans to increase the number of connectors to external sources, which will make collection easier. The architecture is multitenant, with granular permissions-based access. A separate database and access can be created for each matter. Real-time monitoring of process and status reporting is available across the different phases of e-discovery, such as processing, ingestion, indexing, review, and production.

The solution also includes the ability to create, send, and track legal hold notifications, and to track the chain of custody in areas such as collected data and project billing.

Multilevel hierarchical tags are supported, as well as comment fields for different data types, and binder folders for classification, work-product, and document organization. Documents can be classified into various categories using tags.

A number of analytics modules are built in to look at elements such as near duplicates, content-based email threading, images, topical clustering, and PII. eZReview provides automation on various levels, including case setup, templatization, workflow processing, review batching, and assignments. Chat Viewer allows the review of an unlimited number of conversations within a channel, including emojis and shared images. A timeline chart for conversations is available.

ZReview also has a TAR module that can be used for predictive coding or as a continuous active learning (CAL) tool. It is built into the document review solution. Redactions are supported with the ability to apply bulk and inverse redactions. Redaction features can also be customized.

Strengths: Knovos scored well on recursive data parsing, the real-time tracking of e-discovery processes, search, and data governance. These features allow it to manage the e-discovery process from processing to production, as well as ECA. In addition, with its on-premises deployment options, Knovos provides more deployment choices than many of its competitors.

Challenges: Knovos does not currently support audio or video content, but it’s on the roadmap, and Knovos says it intends to provide automated transcription and redaction of media files.

Logikcull

Logikcull is an e-discovery vendor that offers a cloud-based SaaS solution for e-discovery that focuses on the right-hand side of the EDRM. It has 38,000 users worldwide in more than 1,500 companies across 36 countries.

Logikcull provides capabilities from processing to production, and is easy to use with no professional services required. If support services are needed, Logikcull provides 24/7/365 in-app support to all customers for free. It’s targeted at SMBs, law firms, and government entities. Because of its setup, it is best suited to smaller discovery requests involving thousands rather than millions of documents and is, therefore, appropriate for the SMB market.

Logikcull has been designed as a do-it-yourself solution that is quick and easy to download and set up, with a drag-and-drop feature for connecting to a data source if a direct integration is not available. Text and metadata can be automatically indexed to make files searchable, and deduplication, OCR, email threading, and tagging are all included. Important and potentially privileged documents can also be flagged.

Users can search across email, audio and video, Slack, Google, and Microsoft data with intuitive filters that allow users to cull irrelevant documents in bulk. Emails can be filtered by criteria including sender, recipient, and bcc/cc address, and documents can be reviewed, tagged, and redacted individually or in bulk.

Logikcull includes production capabilities that allow documents to be shared in any format with any metadata. Bates numbers can be applied automatically and responses templated, and documents can be shared directly and securely with external parties.

Users can apply legal holds with the ability to preserve Google data in place. Hold notices can be applied and custodian data from Google Workspace can be preserved. A single click turns a hold into a discovery matter, and the drag-and-drop ingestion allows data to be collected from custodians. A number of automated reminders are available, including prompting custodians to accept holds, and they can be scheduled throughout the life of the matter. Holds can be released with a single click.

Review features include tagging and redaction capabilities and fully automated productions. Access to sensitive information can be controlled in a closed-loop environment. External firms can also be given secure access to Logikcull.

Automatic data categorization, deduplication, and email extraction are all supported. Logikcull review works by culling data rather than using predictive coding, and to this end, users filter their data by criteria such as email sender or recipient, document type, keyword, or date range to remove non-relevant content.

Strengths: Logikcull is strong across most of our key criteria areas. Its ability to bulk tag and organize documents helps to group documents and speed up the review process. Recursive data parsing also improves review with a viewer that supports many file formats. The search capabilities allow document volumes to be culled to reduce the manual review effort. Its speed of deployment and its pricing model are differentiators.

Challenges: The major challenge for Logikcull is that its design and simplicity of use makes it unsuitable for enterprises with complex requirements and large volumes of data to review. Moreover, the lack of technology in the review area, such as predictive coding, means that review has to be carried out manually, although the ability to filter and cull data through search goes part way to addressing this.

Microsoft Purview eDiscovery

Microsoft’s path to e-discovery has followed that of other software areas it has moved into: it started with limited capabilities and initially relied on third-party partner products to fill the gaps, and then gradually added the requisite capabilities, either by developing them internally or through further acquisition. Microsoft now has what can be claimed to be an end-to-end e-discovery solution that covers the processes needed to identify, preserve, collect, process, analyze, review, and produce content that is responsive to internal and external investigations.

The solution collects content from Microsoft applications, including Exchange Online, OneDrive for Business, SharePoint Online, Microsoft Teams, Microsoft 365 Groups, and Yammer teams. Data connectors are available to import and archive non-Microsoft data allowing users to apply Microsoft 365 protection and governance capabilities to third-party data. There are over 70 data connectors available, either natively or through Microsoft’s Partner ecosystem. In addition, a new eDiscovery Graph API allows built-in integrations with the broader ecosystem. Three e-discovery Purview solutions are available:

  • Content Search enables the search for content across Microsoft 365 data sources and then exports the search results to a local computer.
  • Microsoft Purview eDiscovery (Standard) provides the ability to identify, hold, and export content found in mailboxes and sites, in addition to the capabilities of Content Search.
  • The Purview eDiscovery (Premium) solution in Microsoft 365 can be used by organizations with a Microsoft 365 E5 or Microsoft 365 E5 subscription (or related E5 add-on subscriptions). This version enables the management of custodians and the analysis of content in addition to the Content Search and Standard solutions.

Purview eDiscovery (Premium) provides search and export capabilities, and allows users to create e-discovery cases and assign managers to each case. Searches and exports can be associated with a specific case, and holds can be placed on content locations relevant to the case. End-to-end workflow is provided to identify, preserve, collect, review, analyze, and export responsive content. Legal teams can manage custodians and the legal hold notification workflow to communicate with custodians. Initial notifications can be created and sent, with reminders and escalations available if custodians do not acknowledge a hold notification.

Review sets can be created, and reviewers are able to filter, search, and tag content to cull non-relevant documents. Analytics and predictive coding models are provided to reduce the manual review effort. Content that’s added to a review set can be tracked and reported on, and when content is added to a review set, there is an option to include cloud attachments or linked files. All versions of a SharePoint document can also be added to the review set. Other features include indexing, OCR, and conversation threading from Teams and Yammer.

Strengths: Microsoft is particularly strong in recursive data parsing and search, which has traditionally been a strength. Its predictive coding models automate much of the review process. It also provides AI capabilities and support for video.

Challenges: The major challenge for Microsoft is in attracting large enterprise customers. It is often regarded as a provider of mid-market or departmental solutions, and its method of adopting a new technology area by initially providing limited capabilities and relying on partner solutions to plug the gaps does not help. Microsoft gradually replaces partner products with capabilities of its own until it has end-to-end capabilities in a particular technology area, which is where it is now with its e-discovery portfolio. However, convincing larger enterprises of this fact may not be easy.

Nextpoint

Nextpoint was founded in Chicago, Illinois, in 2001. It’s entirely cloud based and is sold as a multitenant SaaS solution. Most customers use the per-user subscription model and services as well as the software. More than 95% of sales are direct. Target markets include solo practitioners, midsize law firms, corporate defense firms, and plaintiff class specialists. Although its customers are predominantly SMBs, it has a growing number of enterprise clients, and sells direct to large corporate law departments and government agencies.

Nextpoint provides the ability to upload, review, analyze, produce, and present data. A drag-and-drop uploader is available to import and organize more than 100 file types across multiple platforms. Deduplication, OCR, de-NISTing, email threading, and metadata extraction are all performed automatically. A “file room” is provided with each database to store all uploaded data, which can include briefs, pleadings, and associated case documents.

Searches can be performed by keyword or Boolean search, and preprogrammed search criteria are supplied to help cull unresponsive documents. Documents can be viewed in three formats: image, key terms, and text.

A coding panel provides options for classifying documents as confidential or non-relevant. Checkboxes can be used to set the level of confidentiality, and custom confidentiality classifications can also be created. Privilege codes include attorney-client, work product, and custom fields. Bulk coding of groups of documents with the same characteristics is also supported, and a redaction feature is available.

Once reviewed, documents can be exported in a variety of formats, and users can create custom export templates. Bates numbers can be applied and load files created. Once the export is ready, Nextpoint sends an email to the appropriate parties with a secure link from which the documents in the production can be accessed.

Analytics provide interactive data visualizations, including bar graphs, pie charts, and other visualizations. Clicking on any graph displays a list of the documents in a specific category. Database totals are available for all documents, emails, attachments, and email threads. Clicking on any of these categories will return all corresponding documents. Date ranges can be used to refine database totals. Up-to-date progress of any review regarding relevancy and privilege status is also available. More detailed analytics can be developed by working directly with Nextpoint.

Strengths: Nextpoint has outstanding capabilities in tagging and organizing documents and search, allowing content to be grouped and unresponsive content to be culled, reducing the manual review effort. It also has some presentation capabilities, which many competitors do not have. The solution supports social media and video as data sources, which not all vendors provide.

Challenges: A major challenge for Nextpoint is that it does not deploy predictive coding, which means that search and culling need to be deployed to reduce the manual review effort.

Nuix Discover

Nuix is headquartered in Sydney, Australia, with offices in the US. Its e-discovery suite is called Nuix Discover. At the core of the system is the Nuix Engine, which incorporates processing, review, analytics, and predictive coding. The Nuix product set is available as on-premises software or as a multitenant SaaS in the Nuix cloud. Target markets are large enterprises and legal firms. Nuix provides capabilities across the EDRM.

The Nuix Engine provides processing, search, and analysis for human-generated and machine data, using patented parallel processing, load balancing, and fault tolerance technologies. It handles more than 1,000 data types with new and emerging formats regularly added.

The Nuix Engine processes data across 10 dimensions: communications, databases, digital and mobile forensics, enterprise and cloud systems, human-generated content, log files, multimedia, network captures, real-time and social media feeds, and user and endpoint behavior. It connects directly to file shares, mobile devices, cloud collaboration platforms, email servers, archives, and enterprise applications. Support is also provided for popular cloud storage and collaboration tools including Microsoft 365, AWS, and Google Workspace. An option is available to use Elasticsearch as the database back end.

The Nuix Engine provides load balancing, fault tolerance, and intelligent processing technologies, allowing it to extract text and metadata from virtually all file types at high speed. This is because it includes “worker” bundles that harness processor cores to create a searchable index of the content and metadata for a Nuix case. It also writes subsets of the items in the Nuix case onto disk in the required format.

Keyword, fuzzy, proximity, and regular expression searches are all available to identify terms of interest, and advanced filters such as file type, skin tone, media attributes, custodians, word lists, languages, and named entities allow content to be quickly found.

The investigative analytics and intelligence software enables an understanding of the context and connections between billions of items in the data, and allows users to filter, visualize, and analyze the data. Industry best practices for clustering, mapping, and graphing are included. Advanced data visualizations for client and case-level reporting and tracking and cross-functional e-discovery workflows are also available. Other analytics capabilities include near-duplicate identification and threading. There is also a special gallery view for images and multimedia files, along with the ability to deduplicate content.

Nuix provides predictive coding capabilities through continuous active learning to identify relevance and privilege and to automate much of the review process.

Strengths: This vendor scored well on tagging and organizing documents, search, data governance, and predictive coding. This allows Nuix to be used to manage very large and complex matters, either internally by enterprise legal teams or by legal firms. The Nuix Engine is also a strength and a differentiator and it is used by at least one other e-discovery vendor.

Challenges: Nuix does not provide presentation capabilities, which means it is not an end-to-end solution. As some e-discovery vendors are beginning to add these capabilities, this is considered a limitation.

Onna eDiscovery

Onna was founded in 2015 and is headquartered in New York, US, with offices in the UK and Spain. Its Knowledge Integration Platform provides a central, responsive, and intelligent repository that integrates virtually any data source via APIs and uses ML to analyze any file type. The first product built on the platform was an e-discovery tool designed for legal and IT professionals who needed to undertake litigation, internal investigations, or audits. Onna eDiscovery is primarily targeted at SMBs and large enterprises, but it may apply to some law firms and consultancies, depending on their scope. It is a cloud-based solution, which can be deployed as SaaS or in a single-tenant, managed private cloud. It addresses the left-hand side of the EDRM.

Onna eDiscovery enables the rapid identification, preservation, and collection of data from many popular cloud applications into the centralized Knowledge Integration Platform. Information is aggregated and organized intelligently using ML-driven processing. It is rendered in near-native format, allowing users to find and export the required data for further review. Use cases for the platform include ECA, internal investigations, and due diligence for mergers and acquisitions.

Multiple use cases are supported, including e-discovery (data targeting and identification, processing and collection), archiving, and information governance. Onna eDiscovery is a proprietary application that sits on top of the Onna Knowledge Integration platform. Its e-discovery capabilities can be extended through integration with solutions such as Zapproved to provide legal hold capabilities.

Content can be collected from common cloud applications, including Slack, Google Workspace, Microsoft 365, Jira, Confluence, Box, Zoom, and Zendesk. Collected data can be used across multiple matters. Real-time data transformation, indexing, and information rendering are available. Onna extracts content and metadata from unstructured data, such as threaded Slack and Teams conversations, and displays it in a near-native format.

Standard and custom tagging are supported with tooltips that show how to best use this function. Customer-defined fields are also supported—such as text, long text, number, dropdown, and free tags—which can also be used to organize documents. Search capabilities include regular expressions, Boolean, and proximity searching.

Datasets can be exported to review platforms via common load file formats, including CSV and/or DAT and PDF files. Complex data can be reproduced in a human-readable format. Conversations can be exported with messages threaded by channel, by day, to make them easier to read, and messages can also be exported individually to enable easy redaction.

Strengths: Onna scored well in recursive data parsing, tagging and organizing documents, AI, support for social media content, and support for video content. These capabilities help enterprises to improve the collection of content, perform ECA, and prepare the content for review.

Challenges: Onna is limited in that it only plays on the left-hand side of the EDRM, while most vendors now offer end-to-end capabilities. This makes the solution best suited to SMBs and large enterprises that outsource the review process. Its strategy of relying on a third-party product for legal hold could also be a challenge as it requires additional licensing and will not suit organizations that want to reduce the number of vendors they procure applications from.

OpenText eDiscovery

OpenText is a leading information management vendor that provides solutions across a number of areas. Its portfolio includes digital experience and content services platforms, as well as one of the most comprehensive e-discovery solutions on the market. It also benefits from security products and the company’s Business Network Cloud, which integrates business-to-anything (B2A). Its AI and analytics product Magellan is embedded across its portfolio, including the e-discovery solution.

OpenText’s target markets are law firms of all sizes, corporate legal departments from the Global 5000 across all industries, government entities (municipal, state, and federal), and state-owned enterprises.

OpenText acquired its e-discovery portfolio starting with Recommind in 2016, and it has continued to expand its portfolio, now covering nearly the entire EDRM (minus presentation). The e-discovery portfolio comprises OpenText Axcelerate, OpenText Axcelerate Investigation, OpenText Insight, OpenText Legal Hold, Collection Services, Forensic Services, Recon Investigation Service, Managed Document Review, and Expert Witness. In addition, OpenText offers consulting services. Unlike most of its competitors, OpenText also provides information governance solutions through its content management portfolio.

Deployment options include on-premises, private cloud, SaaS, and hybrid. Axcelerate Portable Solution allows content for review to be isolated to a single location to prevent data from leaving a particular jurisdiction to ensure data sovereignty. The OpenText solution can be used for ECA and supports full-scale discovery.

The OpenText solution starts with OpenText Legal Hold, which is cloud-based litigation hold notification software that enables users to generate, distribute, and enforce legal hold notices; create and manage web-based employee and custodian interviews; create litigation hold workflows; connect to data sources across the enterprise; and automate IT task suspensions.

OpenText Accelerate provides end-to-end e-discovery and investigation capabilities, including collection, processing, analysis, classification, review, and production. Integrated data collection and ingestion is aided by a large collection of connectors that allow data to be collected from on-premises and cloud-based sources. Advanced text analytics support sentiment and entity identification, powered by OpenText Magellan, and predictive filters. TAR provides continuous learning and can reduce manual review by up to 80%. Patterns in documents can be identified and mass redactions, text-select redactions, and pattern redactions applied. Complex field and text searches allow tens or hundreds of millions of documents to be searched.

Axcelerate Visualizer provides an overview of the data sets and all the analytics tools. A hypergraph communications map shows communication networks, and Axcelerate Visualizer Heat Maps depict associations between data and anomalies. There is also a dedicated viewer for chat data.

Strengths: OpenText is strong across the board, and it is still innovating despite being a very well-established vendor. It has outstanding capabilities in recursive data parsing, where it is able to call on technology from elsewhere in its portfolio to provide a viewer. It provides real-time tracking of the e-discovery process so managers can keep an eye on processes in complex matters. It allows the tagging and organizing of document processes to be accelerated using bulk tagging. It also permits search with multiple techniques, data governance with legal holds and redaction, and predictive coding through its TAR capability.

Challenges: An area of weakness for OpenText is its lack of presentation capabilities. Specialist products have provided this in the past, but many e-discovery vendors are adding this to their portfolios. With its information governance capabilities, OpenText could argue that it uniquely offered end-to-end capabilities if it added a presentation module. Moreover, adding speech-to-text transcription, a capability that OpenText already has elsewhere in its portfolio, to its video collection capability would greatly enhance the solution. However, enhanced support for audio-visual formats, including speech-to-text, is a primary development area for OpenText eDiscovery, with significant enhancements planned for release in 2023.

Proofpoint Archive, Proofpoint Discover

Proofpoint is headquartered in Sunnyvale, California, and has offices throughout the US, Canada, Europe (with its European headquarters in Reading, UK), and the Asia Pacific. It is a cybersecurity and compliance risk vendor that aims to protect data and people. It provides an integrated suite of cloud-based solutions to help prevent targeted threats. Proofpoint claims that 75% of the Fortune 100 use its products for people-centric security and compliance solutions that mitigate risks across email, the cloud, social media, and the web. Solutions include email security and protection, cloud security, digital risk protection, compliance and archiving, and e-discovery.

Proofpoint Archive provides built-in e-discovery capabilities, including search features, litigation hold, collection, review, and export. Proofpoint Discover is an add-on that automates the search and review task and helps to visualize search criteria results. ML is used to help determine responsive content.

Case management allows individual e-discovery elements to be organized, including searches, holds, and folders. These are all put into a case, which enables tracking and visibility. The case management dashboard provides a view of all aspects of the e-discovery case, including highlights of the status of tasks, key dates to consider, a list of which custodians are involved, and related review sets and export details. There is also a search within search feature to perform enhanced data culling to get to relevant messages. In addition, users can be given access to only the data that is relevant to their case.

Proofpoint Discover provides analytics, dashboards, and conversation threading to see communications as they happen, and includes visualization features. The solution also features interaction analysis that gives users an understanding of key custodians and patterns worth investigating. Search criteria can be defined using topic clustering and timeline graphing, and search can be used to cull content prior to review.

Proofpoint Discover includes TAR, which uses ML algorithms to automate much of the review process by deciding whether archived documents are responsive or not, based on human assessment. This reduces the amount of human review required for documents deemed as non-responsive. The final result set can then be exported to a presentation solution.

The Query Analytics feature is designed to help users focus on the relevance of their searches. It provides PDF reports that display the impact of a query and shows counts of items that match search criteria and the impact of removing specific search criteria. These reports can also provide proof of query terms and results.

Strengths: Proofpoint’s strongest area is its search capability, a major feature throughout its portfolio. It also supports social media data sources and other internet-based sources. Although e-discovery is not a major focus of Proofpoint, it nevertheless provides a decent level of functionality.

Challenges: Proofpoint’s e-discovery capabilities are buried among its other more prominent products. If the company wants to sell e-discovery to new customers, it needs to make its product more visible.

Relativity RelativityOne

Relativity is a well-established e-discovery vendor. It is headquartered in Chicago, Illinois, US, but has a global presence with offices in Poland, Australia, China, and the UK.

RelativityOne provides capabilities for collection, processing, review, and production, and analysis. There is also a legal hold product. RelativityOne is available as a SaaS solution.

Relativity Legal Hold automates notices, preservations, and email communications. It includes a library of templates for creating hold notices. A complete audit trail is included of every action, and it also tracks every legal hold action from hold notice to release.

RelativityOne collects data across multiple cloud sources and can add custodians. There are connectors to a growing number of data sources, including Box, Google Drive, Google Chat, Gmail, Google Groups, OneDrive, Outlook, Teams, Slack, and X1.

Filters are provided to allow users to quickly prioritize and process the data relevant to the matter. Documents collected, including associated metadata, can be processed directly into the review workspace.

Review and production capabilities include the ability to automate and customize workflows. Custom placeholders can be created, multiple markup sets are available, and documents can be pulled or replaced easily. Automatic redactions are available, and extensive visualization capabilities allow communication patterns and related concepts to be viewed to uncover trends. Data types can be examined in their native formats and collaboration data reviewed as a conversation, and can include emojis, reactions, attachments, edits, and deleted messages to assess sentiment.

Relativity Analytics provides an extensive range of features that help users to identify and group relevant documents based on criteria such as similar or nearly identical documents, in which case the software also provides a percentage of similarity. Email threading, language identification, categorization, and clustering are also available.

TAR provides a choice of active learning or sample-based learning. The active learning workflow uses ML to continuously assess what is important in documents. Documents are coded, and active learning locates the most relevant ones.

Sample-based learning requires a seed set of documents, and it suggests coding. The documents that are coded as responsive are then sent to reviewers, where the accuracy of the review decision is checked.

Relativity provides extensive ECA features that allow users to view information such as file formats, volume of documents, and date ranges, as well as custodians, search terms, and concepts, to estimate the scope and cost of a case.

Strengths: Relativity’s strongest features are in tagging and organizing documents, search, data governance, and predictive coding, and these features help to streamline complex matters. It’s best known for its review capabilities, and integrates with e-discovery products that either specialize in or have stronger capabilities on the left-hand side of the EDRM.

Challenges: Relativity is weak in support for social media and internet sources and it does not support collection from video sources. These are areas that the company needs to address if it wants to become a Leader.

Veritas Advanced eDiscovery (SaaS) and Veritas eDiscovery Platform

Veritas Technologies, headquartered in Santa Clara, California, US, is a provider of multicloud data management solutions that include backup, archiving, e-discovery, and analytics. It claims more than 80,000 customers, including 87% of the Fortune Global 500. Veritas supports more than 800 data sources, 100 operating systems, 1,400 storage targets, and 60 clouds, and has made strategic acquisitions to expand its portfolio. It acquired Clearwell for e-discovery in 2011, so it is well-established as an e-discovery vendor. It has since enhanced its capabilities with the acquisition of Globanet in 2020, which included Merge1, enabling it to improve its collection capabilities.

Veritas provides end-to-end e-discovery on-premises, in the customer’s tenancy, and in a multitenant SaaS solution. This modular solution covers legal hold and preservation, identification and collection, preprocessing and processing, search, review, production, and export. Target markets are SMBs, large enterprises, public sector organizations, and legal firms.

Veritas offers two versions of its software:

  • Veritas Advanced eDiscovery is a multitenant, SaaS-based, end-to-end e-discovery solution that enables organizations to collect, review, and produce ESI.
  • Veritas eDiscovery Platform is an enterprise e-discovery solution for enterprises, governments, and law firms to manage legal, regulatory, and investigative matters. It can be deployed in-house or hosted by a certified service provider.

Modules within the e-discovery portfolio include Merge1, which allows more than 120 data sources to be collected, including email, collaboration, chat, and transcribed voice and video. Veritas Data Insight handles the proactive assessment and mitigation of unstructured and sensitive data security risks, providing an analysis of the content in near real time. It also allows sensitive content to be classified.

Veritas offers extensive search capabilities, including Boolean, proximity, fuzzy, and nested searches. Sentiment is also identified. Search is enabled across indexed text, as well as multimedia files (audio and video) to include phonetic searching and transcription searching. It can also search against its archive—Enterprise Vault and Enterprise Vault.cloud, and can leverage additional search techniques, including custom message attributes, retention tags, and social tags.

An important review feature for Veritas is its ECA tool technology, which allows much of the review process to be accelerated by leveraging AI and classification, reducing the amount of manual review required. One way of achieving efficiency is to apply the Veritas ML models at the time of collection/ingestion, which cuts down on the amount of data that needs to be collected, providing just the data that needs to be reviewed.

Strengths: Veritas has outstanding capabilities in recursive data parsing, real-time tracking of the e-discovery processes, and tagging and organizing documents, where it can tag using ML, search, and data governance. This allows it to handle multiple complex matters simultaneously, making it well-suited to large enterprises.

Challenges: Veritas does not currently offer presentation capabilities, preventing it from providing true end-to-end capabilities. However, adding presentation functionality is on the roadmap.

Zapproved ZDiscovery Platform

Zapproved was founded in 2008 and is headquartered in Portland, Oregon. It offers e-discovery software that covers the entire EDRM for enterprise legal teams, where it has more than 350 corporate customers. Deployment is SaaS only, and licensing is based on an annual subscription. Typical use cases include legal hold management (notifications, tracking, escalations, and reporting), routine litigation (discovery response), internal investigations, ECA, subpoena response (records requests and third-party information requests), data processing and culling, document review, and document production (imaging, Bates numbering, and endorsements).

Zapproved’s e-discovery solution, ZDiscovery, can be deployed as separate modules or as an integrated suite. The modules are ZDiscovery Hold, ZDiscovery Preserve, ZDiscovery Collect, and ZDiscovery Review. Capabilities include legal holds, in-place preservation, automated collections, processing and review, and task management.

Users can create, send, modify, and track legal holds, with the ability to automate tasks such as custodian interviews and hold reminders. Integration with the existing legal tech ecosystem—including HRIS, matter management systems, and other enterprise applications—is enabled. Reporting and audit trails provide insights and visibility across matters. The ZDiscovery Tasks module allows matter milestones to be tracked.

Data in applications such as Microsoft 365, Google Vault, and Slack can be preserved with a single click. An automated audit trail records every action, and there are no volume limits to the amount of custodian data or hold issuances. When a hold is released, the preservation is automatically lifted.

Data can be collected directly from Microsoft 365 using certificate-based authentication, and filters can be applied to conduct targeted searches. Lucene-based search, built on the Elasticsearch engine, powers the search capability. Real-time progress metrics allow collection statuses to be tracked, and a post-collection error report is provided.

Data can be pushed into ZDiscovery Review for processing and review either via automated collections (Microsoft 365) or through a simple drag-and-drop portal, which is provided to ingest data. Thousands of data types are supported, including Encase, Spanned Encase, and FTK files. Automatic de-NISTing and deduplication occur on ingestion, and filtered searching during processing can further reduce the number of documents to review. Redactions are supported. Zapproved uses search techniques and filtering to reduce the volume of documents to review. Although it uses the Nuix processing engine, it does not offer predictive coding techniques.

Bates numbering and other configurable endorsements can be applied to documents, and files can be exported in native, TIFF, and PDF formats with configurable metadata columns.

Strengths: Zapproved scored well on recursive data parsing and search, which support the collection, processing, and review of content from many different sources. It supports social media and video, further increasing the number of sources it can collect from. The depth of its capabilities—including its strength in the areas of legal hold and data preservation management—makes it suitable for enterprises and SMBs to use internally to address everyday compliance and regulatory issues as well as internal investigations.

Challenges: A challenge for Zapproved is that it does not use predictive coding, and while review sets can be reduced a lot through search and culling, there could still be large numbers of documents that need to be manually reviewed.

6. Analyst’s Take

The e-discovery market is characterized by three distinct user categories:

  • Organizations that conduct the initial searches in-house and outsource the review process
  • Law firms that conduct review work on behalf of enterprise and SMB clients
  • Large enterprises with huge legal teams that conduct the entire e-discovery process in-house

This means that three types of products are required:

  • Solutions that address the left-hand side of the EDRM and provide identification, preservation, collection, and (sometimes) processing capabilities
  • Solutions that address the right-hand side of the EDRM and provide (sometimes) processing, review, analysis, and production capabilities
  • Solutions that provide end-to-end capabilities

It should be noted that while some vendors claim to provide capabilities for presentation, often, these amount to little more than producing Bates numbering and supporting a variety of formats for export to presentation solutions. A few vendors do provide true presentation capabilities, and more have it on their roadmap.

Looking at the vendors in this report, IBM and Onna focus on the left-hand-side of the EDRM; Consillio, Digital WarRoom, Knovos, and Logikcull address the right-hand side of the model; and CloudNine, DISCO, Everlaw, Exterro, IPRO, Microsoft, Nextpoint, Nuix, OpenText, Proofpoint, Relativity, Veritas, and Zapproved provide end-to-end capabilities.

It is important to select the right type of product to address your specific requirements. There is little point in paying for capabilities that will never be used. Some end-to-end vendors provide modular products, which means you can implement just the required modules, rather than the entire platform. These modules can then be integrated with third-party solutions, allowing enterprises to create a best-of-breed solution.

Some e-discovery solutions are best suited to large discovery requests where huge volumes of content are involved, and the enterprise typically has multiple matters in progress at any one time. These solutions will offer professional services as well, and enterprises will likely need to take advantage of them, at least in the early stages of use. At the other end of the scale are solutions that emphasize ease of use, and these are generally more suited to single matters with lower volumes of content. While most vendors claim to target large enterprises, some are more suited to the SME market. It is, therefore, important to consider the number of simultaneous cases supported and note any restrictions on scalability when selecting a platform.

Finally, also consider the deployment model. Some solutions are SaaS-only, and may only offer a multitenant option. Some are more flexible and offer private cloud options, but only a few still provide a traditional on-premises software solution.

7. About Sue Clarke

Sue Clarke

Sue Clarke has worked as an industry analyst for almost 25 years, supplying research, analysis, and advisory services in the content management space to both organizations and vendors. She has built up a wealth of knowledge and experience having spent more than 20 years focusing on enterprise content management (ECM), in areas including document management and collaboration, records management, enterprise file sync and share, search, content analytics, case management/business process management, capture and scanning, e-discovery, web content management, digital asset management, web analytics, and customer communications management.

8. About GigaOm

GigaOm provides technical, operational, and business advice for IT’s strategic digital enterprise and business initiatives. Enterprise business leaders, CIOs, and technology organizations partner with GigaOm for practical, actionable, strategic, and visionary advice for modernizing and transforming their business. GigaOm’s advice empowers enterprises to successfully compete in an increasingly complicated business atmosphere that requires a solid understanding of constantly changing customer demands.

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GigaOm’s perspective is that of the unbiased enterprise practitioner. Through this perspective, GigaOm connects with engaged and loyal subscribers on a deep and meaningful level.

9. Copyright

© Knowingly, Inc. 2022 "GigaOm Radar for E-Discovery" is a trademark of Knowingly, Inc. For permission to reproduce this report, please contact sales@gigaom.com.