Ratings and Reviews 5 Ratings
Ratings and Reviews 0 Ratings
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Maestro PaymentOur platform was specifically designed to tackle the unique difficulties faced in making payments to international contractors, freelancers, and vendors. Unlike traditional systems that can take weeks or even months to implement, our setup and user onboarding can be accomplished in just one hour. The immediate benefits of reduced transition costs and time savings from automation are evident right away, rather than being delayed for months or even years. By automating processes, we significantly decrease the chances of fraud and minimize errors. Additionally, our software features automatic invoice validation, which cross-references invoices with contracts and work hour reports to ensure precise billing. It also incorporates approval workflows, delineates responsibilities, and further mitigates the risk of fraudulent activities. Ultimately, our solution streamlines payment management while enhancing security and efficiency.
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QuaerisTailored results will be delivered to you based on your preferences, past experiences, and specific role. QuaerisAI ensures that you have access to data that is almost in real-time for all your data needs. The platform boosts your data and document management tasks by leveraging AI technology. To foster knowledge exchange and monitor progress, teams have the ability to share insights and create pinboards. Our sophisticated AI engine swiftly converts your inquiries into a format suitable for database processing within mere seconds. Just as life requires context, so does data; our intelligent AI engine analyzes your search terms, interests, roles, and historical data to rank results that encourage deeper exploration. Additionally, you can effortlessly apply filters to your search outcomes, allowing you to uncover specific details and delve into pertinent questions that arise. This seamless integration of AI not only enhances efficiency but also enriches the overall user experience.
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What is Docskiff Smart Contract Analytics?
Smart Contract Analytics (SCA) is an advanced platform dedicated to Contract Discovery and Analytics, harnessing the power of Artificial Intelligence and Machine Learning to provide users with a holistic overview of contracts and related documents. This innovative platform enables organizations to extract, assess, and analyze vital information, thereby facilitating informed decision-making processes.
The product boasts several key features, including the use of NLP and deep learning techniques to efficiently extract metadata. Additionally, users can export data to Excel or other preferred formats and seamlessly integrate it into any CLM or downstream system. The ability to develop dynamic machine learning models tailored to specific contract types enhances its analytical capabilities. Moreover, the platform is equipped with adapters that connect to various data sources, allowing the retrieval of legacy documents from locations such as FTP, Google Drive, SharePoint, Dropbox, and S3. It also categorizes contracts by type—such as MSA, NDA, or SOW—ensuring streamlined organization. Lastly, its document OCR functionality allows for the conversion of images, PDFs, and scanned documents into editable text, further enhancing accessibility and usability. This combination of features makes SCA an invaluable tool for organizations aiming to optimize their contract management processes.
What is Gimmal Discover?
The goal is to identify, categorize, and oversee data to safeguard sensitive information while minimizing privacy concerns. Gimmal Discover is capable of integrating with diverse corporate data sources, including file shares, PST files, and local workstations. Additionally, it supports platforms like Exchange, SharePoint, OneDrive, Box, and Google Workspace, among others. If sensitive data, such as personally identifiable information (PII), is not properly managed, it risks being overlooked within these data repositories, leading to significant privacy or compliance challenges. By identifying sensitive files, Gimmal Discover plays a crucial role in lowering these risks and provides solutions for their management. Its robust eDiscovery features can significantly aid legal teams in their processes. Furthermore, Gimmal Discover enables the application of classification categories to ensure content aligns with your organization’s information governance policies, thereby enhancing overall compliance and security. This comprehensive approach ultimately fosters a more secure data environment for organizations.
Integrations Supported
Box
Conga CLM
EraCLM
Google Workspace
Microsoft Exchange
Microsoft OneDrive
Microsoft SharePoint
Salesforce
Integrations Supported
Box
Conga CLM
EraCLM
Google Workspace
Microsoft Exchange
Microsoft OneDrive
Microsoft SharePoint
Salesforce
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Standav Corp
Date Founded
2009
Company Location
United States
Company Website
www.docskiff.ai
Company Facts
Organization Name
Gimmal
Date Founded
2002
Company Location
United States
Company Website
www.gimmal.com/gimmal-discover/
Categories and Features
eDiscovery
Case Analytics
Compliance Management
Discussion Threads
Document Indexing
Document Tracking
Full Text Extraction
Keyword Search
Metadata Extraction
Topic Clustering
Categories and Features
eDiscovery
Case Analytics
Compliance Management
Discussion Threads
Document Indexing
Document Tracking
Full Text Extraction
Keyword Search
Metadata Extraction
Topic Clustering