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Average Ratings 0 Ratings
Description
Sutherland Extract is an advanced OCR solution driven by AI that evolves by learning from exceptions, enhancing its intelligence over time. This robust platform facilitates cognitive data extraction from input to output, effectively tackling the operational hurdles encountered in document-centric workflows. It integrates smoothly with robotic process automation tools and a variety of applications within your business framework. Access to data is vital for businesses to succeed, and that data must be available, pertinent, and actionable. Unlike conventional Optical Character Recognition (OCR) systems that impose limitations on digitization success, our AI-driven extraction platform can easily link with your current applications to boost efficiency. Traditional OCR approaches demand extensive rules and templates for every unique document format, resulting in a reliance on human input and lengthy processing times. In contrast, Sutherland Extract employs sophisticated deep learning technology that comprehends document structures, significantly enhancing Straight-Through Processing (STP) through intelligent data extraction and cognitive automation. This innovative approach not only streamlines workflows but also empowers organizations to make more informed decisions based on reliable data insights.
Description
reciTAL is a pioneering software company specializing in Artificial Intelligence, recognized as the first player in Intelligent Document Processing with a Deep Tech designation. This innovative platform streamlines the extraction, classification, and searching of various document and email flows through automation. Users have the flexibility to re-train models at any point, incorporating insights from user feedback to enhance accuracy. The expert team at reciTAL supports clients in deploying the software within their own Kubernetes environments or through Docker Compose. Setting up fundamental business rules is quick and straightforward, allowing for efficient configuration of essential data points. Based on the confidence level achieved, an operator determines whether the extracted data is validated. The process of configuring a new document type is remarkably fast and user-friendly, and the validated data contributes to ongoing enhancements in performance. This continuous feedback loop ensures that reciTAL evolves to meet the changing needs of its users effectively.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Gmail
Google Drive
Microsoft Azure
Microsoft Outlook
Microsoft SharePoint
Integrations
Amazon Web Services (AWS)
Gmail
Google Drive
Microsoft Azure
Microsoft Outlook
Microsoft SharePoint
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
Sutherland
Founded
1986
Country
United States
Website
www.sutherlandglobal.com/products-x-platforms/sutherland-extract
Vendor Details
Company Name
reciTAL
Founded
2017
Country
France
Website
recital.ai/en/
Product Features
Data Extraction
Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction
Product Features
Data Extraction
Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction
Enterprise Search
AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery