OpenText™ eDiscovery
Gain control over e-discovery and alleviate legal risk
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Description
OpenText™ eDiscovery is a fully integrated end-to-end e-discovery solution that delivers best-in-class capabilities to help legal teams get to the facts sooner and inform case strategy. With advanced analytics, technology-assisted review, and generative AI, OpenText eDiscovery empowers legal teams to be more proactive, productive, and powerful.
Benefits
How OpenText eDiscovery can benefit business
Discover the advantages of using OpenText eDiscovery.
- Speed projects and lower costs – Prioritize the most likely relevant documents for review via continuous machine learning and reduce volumes needing eyes-on review to improve efficiency and accuracy.
- Protect and secure personal data – Protect personal data with automated detection and redaction based on a pre-configured library of common patterns, custom RegEx and automated QC.
- Optimize with expert services – Leverage expert services to expedite projects and optimize results from data collection and forensics to managed review, investigations and eDiscovery advisory services.
- Enhance collection efficiency – Crawl and collect data wherever it resides, from ECM systems to email, cloud repositories and more.
- Conduct Early Case Assessment (ECA) and investigations – Gain rapid insight for faster case strategy with front-ended analytics for true ECA at the earliest stage of a matter.
Differentiators
Why OpenText eDiscovery?
- Integrated eDiscovery solution – Collect, process, analyze, review and produce electronically stored information (ESI) across the EDRM in a single platform.
- Flexible deployment options – Deploy on-premises, in a private cloud, OnDemand, as a managed service or portable appliance for data that needs to stay onsite, or in a hybrid environment.
- Proprietary analytics and generative AI – Accelerate review and analysis with advanced text analytics – including automated sentiment and entity identification – and AI-generated key document and concept group label summaries.
Features
- Generative AI powered review – Lowers costs and increases speed to facts by using OpenText Aviator GenAI to automate review. Delivers cost certainty and transparency with up-front large language model cost estimates and the ability to test review criteria on a sample data set.
- Data collection and processing – Fuels efficiency via 45+ data source connectors as well as automated deduplication and de-NISTing. Balances over-collection and under-collection for optimal efficiency with refined search criteria.
- Technology-assisted review – Surfaces documents with similar content for prioritized review to accelerate projects, dramatically reducing costs and concern over missing documents for productions, investigations, ECA, witness and issue preparation or privilege QC.
- Text analytics – Empowers rapid insights with automated identification of people, places, and organizations, document summaries for context, sentiment analysis for attitude and emotion, and fact vs. opinion analysis to test assertions.
- AI-generated summaries – Improves case and review strategy and prioritization by using OpenText Legal Tech Aviator – the central AI nervous system of the OpenText smart legal platform – to deliver insight into key evidence and concept groupings.
- Pre-review analytics – Dramatically reduces data volumes warranting eyes-on review with extensive smart filters, automated concept grouping, phrase analytics, front-loaded text analytics, and predictive filters that create highly refined review sets.
- Visualizer and hypergraph communications map – Uncovers hidden data and communication patterns, quickly surfacing key evidence and additional custodians and witnesses, while seeing associations between data to ensure nothing is overlooked.
- Accurate productions and case management integration – Allows users to easily and reliably produce document sets with a production wizard, templates, and automated QC of contents and redactions. Ensures that the key data uncovered during review is reliably included in case management processes.