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Average Ratings 0 Ratings
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 Moreover, re-papering outdated licenses ensures adherence to new regulatory standards and customer demands, while guaranteeing that quality reviews and documentation are meticulously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
Have your contracts assessed in just a few hours, eliminating the need to wait or repeatedly contact your attorney. Leverage insights from previous agreements alongside current market dynamics to secure the most favorable deals possible. Enjoy comprehensive contract services through a single, clear, fixed-price plan that has no hidden costs. Superlegal specializes in negotiating essential sales agreements that are often costly and time-consuming. We handle thousands of negotiations at once, allowing us to scale alongside your business growth. Our commitment ensures turnaround times as quick as 4 hours, all while providing savings of up to 90%. Powered by advanced AI, Superlegal uses a wealth of contract data, which has been meticulously refined by legal professionals. This technology not only processes aggregate data from your contracts but also establishes guidelines for future negotiations, assisting you in spotting opportunities, obligations, and potential liabilities, ultimately streamlining your contract management process.
API Access
Has API
API Access
Has API
Integrations
Dropbox
Google Drive
Microsoft SharePoint
Automation Anywhere
Box
HubSpot CRM
HubSpot Customer Platform
Microsoft Excel
Microsoft OneDrive
Microsoft Word
Integrations
Dropbox
Google Drive
Microsoft SharePoint
Automation Anywhere
Box
HubSpot CRM
HubSpot Customer Platform
Microsoft Excel
Microsoft OneDrive
Microsoft Word
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$999 per month
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
Docugami
Country
United States
Website
www.docugami.com
Vendor Details
Company Name
Superlegal
Country
United States
Website
www.superlegal.ai/
Product Features
Text Mining
Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering