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Description
Eve is an all-encompassing AI-driven legal platform tailored for plaintiff law firms, streamlining every phase of a legal case from initial intake to final resolution. It starts with the case intake and assessment process, assisting firms in pinpointing cases with the highest potential and generating concise overviews based on critical documents and facts. In the pre-litigation stage, Eve is capable of drafting various legal documents in the desired tone and style, including demand letters, medical chronologies, and complaints, while referencing pertinent case facts. As litigation progresses, it offers support by propounding discovery, addressing discovery requests, analyzing depositions, and formulating motions, accomplishing these tasks in mere minutes rather than hours. Eve is designed to seamlessly integrate with existing workflows and adapt to the specific processes of each firm, moving away from generic legal automation to a collaborative system that “works alongside you.” Additionally, it boasts features such as an AI reasoning mode for sophisticated legal analysis, inline source citations, and a robust validation framework to ensure the accuracy of its outputs. By enhancing efficiency and accuracy, Eve empowers law firms to focus more on strategy and client interactions.
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.
API Access
Has API
API Access
Has API
Integrations
Persona
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
Eve Legal
Country
United States
Website
www.eve.legal/
Vendor Details
Company Name
Intraspexion
Founded
2016
Country
United States
Website
intraspexion.com/mvp