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Description

The annual expenses associated with commercial tort litigation targeting businesses, which encompass benefits paid, losses, legal fees, and administrative expenditures such as document collection and attorney meetings, were estimated at around $160 billion, culminating in nearly $1.6 trillion over the course of a decade. To create a deep learning model focused on the federal court’s civil rights-employment category, specifically "employment discrimination," we gathered factual allegations from 400 federal court complaints—excluding any email data. This model was deployed on GPU instances within Microsoft Azure and AWS, where it was evaluated using 20,401 emails from the Enron dataset, marking the first instance the model encountered email data. Each identified true positive email can be exported to a platform for internal investigations or case management purposes, enhancing the model’s utility. Furthermore, with an integrated database connected to the user interface, users have the capability to save these true positives, incorporate them into the initial training set, and subsequently re-train the model for improved accuracy and performance. As a result, this continual learning process ensures that the model evolves and adapts over time to better identify relevant cases.

Description

The realm of eDiscovery and investigations is rapidly being transformed by artificial intelligence. In partnership with Brainspace, we have unified our efforts to deliver a platform consistently enriched with the latest advancements in AI and machine learning. Reveal Review stands out as the most all-encompassing document review solution, equipped with the versatility and capacity to handle any legal challenge, no matter its complexity or scale. Given the plethora of tools available to enhance and streamline the review process, it is essential to have a review instrument that offers seamless capabilities for searching, filtering, and organizing documents, thereby allowing you to effectively oversee the process from batching to production. We designed our eDiscovery platform with our own needs in mind, prioritizing speed, efficiency, and user-friendliness while eliminating the frustrations often associated with other options. Additionally, Reveal clients benefit from immediate access to pre-trained AI models that can be integrated into their workflows, effectively addressing the initial hurdles that arise during reactive litigation and investigations. This commitment to innovation ensures that users are always equipped with the best tools for their legal needs.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Intraspexion

Founded

2016

Country

United States

Website

intraspexion.com/mvp

Vendor Details

Company Name

Reveal

Founded

2008

Country

United States

Website

www.revealdata.com

Product Features

Product Features

Data Discovery

Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics

eDiscovery

Case Analytics
Compliance Management
Discussion Threads
Document Indexing
Document Tracking
Full Text Extraction
Keyword Search
Metadata Extraction
Topic Clustering

Alternatives

Alternatives

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Trellis.law

Trellis Research
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Digital WarRoom

DWR eDiscovery