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Description
Document engineering provides immediate benefits to business users right from the start, eliminating the need for extensive investments in machine learning, extensive employee training, or significant IT development. It allows for the analysis of agreements to identify potential risks, pricing structures, and contractual obligations. By doing so, organizations can prevent costly penalties and escalated fees that result from delays. This approach enables the conversion of carrier plans into usable data, allowing brokers to concentrate on sales rather than data entry tasks. Additionally, it helps reduce expenses while enhancing quality compared to relying on temporary staffing solutions year after year. Thoroughly examining your Master Service Agreements and Statements of Work reveals deliverables, pricing structures, liabilities, and legal risks, mitigating the chance of unexpected costs. It also streamlines the diligence process during transactions, helping to pinpoint price discrepancies, renewal timelines, sub-lease options, and tax complications across entire portfolios. Compliance with tax regulations becomes easier, rents can be optimized, and unnecessary fees can be avoided. By unlocking the data embedded in your unique documents, productivity, compliance, and insights can be significantly enhanced. Moreover, re-papering outdated licenses ensures adherence to new regulatory standards and customer demands, while guaranteeing that quality reviews and documentation are meticulously maintained for future reference. Ultimately, this comprehensive approach empowers organizations to navigate complex documentation with confidence and clarity.
Description
Quickly extract essential provisions and data from countless documents within minutes, eliminating the tediousness and errors associated with traditional contract reviews.
What enables eBrevia to achieve this efficiency? The integration of natural language processing technology with machine learning, a branch of AI dedicated to understanding algorithms. This advanced contract analysis software utilizes a vast database of numerous legal documents to detect linguistic patterns and pinpoint critical concepts effectively.
Introducing eBrevia DraftPro, an innovative AI-driven platform that revolutionizes and streamlines how your legal team and other organizational staff draft, negotiate, manage, execute, and analyze agreements.
Our contract analytics software features a comprehensive library of pre-trained provisions, allowing it to automatically extract data for many of the concepts and key data points you require. This is merely the starting point of its capabilities, promising even greater advancements in efficiency and accuracy.
API Access
Has API
No
API Access
Has API
No
Integrations
Automation Anywhere
Yes
Dropbox
Yes
Google Drive
Yes
Microsoft Excel
Yes
Microsoft OneDrive
Yes
Microsoft SharePoint
Yes
Microsoft Word
Yes
UiPath
Yes
Zapier
Yes
Integrations
Automation Anywhere
No
Dropbox
No
Google Drive
No
Microsoft Excel
No
Microsoft OneDrive
No
Microsoft SharePoint
No
Microsoft Word
No
UiPath
No
Zapier
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Docugami
Country
United States
Website
www.docugami.com
Vendor Details
Company Name
eBrevia
Founded
2011
Country
United States
Website
www.ebrevia.com
Product Features
Text Mining
Boolean Queries
No
Document Filtering
No
Graphical Data Presentation
No
Language Detection
No
Predictive Modeling
No
Sentiment Analysis
No
Summarization
No
Tagging
No
Taxonomy Classification
No
Text Analysis
No
Topic Clustering
No
