Advanced Analytics & AI
Document review conducted without advanced analytics is slower, more expensive, and more likely to miss critical evidence than review that integrates the right technology from the outset. In matters involving millions of documents, the difference between a well-designed analytics workflow and a purely manual one is measured in months of review time and millions of dollars in cost. It is also measured in the quality and completeness of the findings. Gemean offers multiple analytics options to ensure the most defensible and efficient document review possible. With proven technologies such as email threading, clustering, communications analysis, and concept searching, Gemean can provide early insights into large document sets.
PythAI
Gemean also continues to offer active learning and technology assisted review workflows to identify relevant documents and reduce review times. Our team has a lengthy track record of proven accuracy and dependability.
Early Case Assessment
Gaining an informed understanding of the scope, key facts, and strategic landscape of a matter as early as possible changes how effectively resources are allocated across the entire engagement. Gemean's e-discovery data analytics and PythAI platform allow legal teams to gain meaningful insights into large document populations quickly, identifying key custodians, relevant time periods, important communications, and potential issues before the full review process begins.
First Level Review
First level review is where the bulk of review time and cost is concentrated in any large matter. Gemean's managed eDiscovery services integrate PythAI and technology-assisted review workflows to reduce the volume of documents requiring human review at the first level, improve coding consistency, and ensure that relevant and privileged documents are identified accurately and efficiently across even the largest and most complex document populations.
Analysis of Opposing Productions
Understanding what the opposing party has produced, identifying gaps, and surfacing the documents most significant to the matter requires more than manual review. Gemean's ediscovery forensics experts apply advanced analytics and PythAI to opposing productions, delivering structured, strategic analysis that gives legal counsel a faster and more thorough understanding of what the other side has provided and what it means for the matter.
Quality Control for Document Review
Quality control is not a final step. It is an integrated process that runs throughout the review and ensures that coding decisions are consistent, accurate, and defensible from beginning to end. Gemean's enterprise eDiscovery services team uses PythAI and advanced e-discovery data analytics to identify inconsistencies, flag outliers, and continuously validate the accuracy of the review as it progresses, delivering a quality-controlled result that holds up under challenge.
TESTIMONIAL
Gemean understood the legal context as well as the forensic one. They knew what the regulators would focus on, what outside counsel needed, and how to structure the findings to serve both. That combination is not easy to find.
PythAI Platform Advantage
Proven Analytics Technology
Early Case Insights
Defensible Review Workflows
The right analytics workflow changes
the economics of document review entirely
What is the role of advanced analytics in eDiscovery?
Advanced analytics in electronic discovery services encompasses a range of technologies and techniques designed to reduce review volume, improve consistency, surface relevant evidence earlier, and deliver more defensible results than purely manual review. In matters involving large document populations, analytics is not optional. It is the primary mechanism by which review time and cost are controlled without sacrificing the quality or completeness of the findings.
What is PythAI and how does it work?
PythAI is Gemean’s proprietary platform for document review and interrogation. It applies artificial intelligence to the document review process to deliver meaningful cost and time savings across a range of use cases including early case assessment, first-level review, analysis of opposing productions, and quality control. PythAI is designed to meet the defensibility standards that legal and regulatory matters require, combining the speed and thoroughness of AI with the documented methodology that courts and regulators expect.
What is technology-assisted review and is it defensible?
Technology-assisted review, also known as predictive coding or TAR, is a workflow in which an AI model learns from reviewer decisions and applies those decisions consistently across a large document population. It is well-established in the industry and has been accepted by courts in numerous jurisdictions as a defensible approach to document review when properly implemented and validated. Gemean’s ediscovery forensics experts have a lengthy track record of implementing technology-assisted review workflows that meet the defensibility standards courts and regulators apply.
What is early case assessment and how does analytics support it?
Early case assessment is the process of gaining an informed understanding of the scope, key facts, and strategic landscape of a matter as early as possible. Gemean’s e-discovery data analytics and PythAI capabilities allow legal teams to gain meaningful insights into large document populations quickly, identifying key custodians, relevant time periods, important communications, and potential issues before the full review process begins. This early visibility enables better strategic decisions and more efficient resource allocation across the matter.
How does email threading reduce review time and cost?
Email threads are among the most duplicative data types in a large document population. Without threading, reviewers may code the same email conversation multiple times across multiple individual messages. Gemean’s email threading technology organizes email conversations into complete, chronological threads and identifies the most inclusive version of each thread, significantly reducing the number of documents requiring individual review and ensuring that reviewers see the full context of every communication.
How does concept searching differ from keyword searching?
Keyword searching finds documents that contain the specific terms included in the search query, regardless of context or meaning. Concept searching finds documents that contain ideas and concepts related to the search objective, regardless of the specific language used. In practice, concept searching surfaces documents that are relevant but do not contain the exact keywords anticipated, significantly improving the recall of the review process and reducing the risk of missing critical evidence.
How does Gemean validate the accuracy of its analytics and AI workflows?
Validation is a core component of every analytics and AI workflow Gemean deploys. Our managed eDiscovery services team applies established validation methodologies to confirm that the workflow is performing at the accuracy levels required by the matter, and we document the validation process in a way that is transparent and reproducible. This documentation is critical to demonstrating the defensibility of the review process if it is challenged by opposing counsel or scrutinized by a court.