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What is NetOwl Extractor?
NetOwl Extractor offers highly accurate, fast, and scalable entity extraction in multiple languages by leveraging advanced AI-powered natural language processing and machine learning methods. This tool for named entity recognition can be deployed both on-premises and in cloud environments, making it suitable for a broad spectrum of Big Data Text Analytics applications. With support for over 100 unique entity types, NetOwl delivers a robust semantic ontology for entity extraction that outperforms traditional named entity extraction solutions. It encompasses a variety of entities, including people, multiple categories of organizations (like corporations and government bodies), various geographic locations (such as countries and cities), and also includes addresses, artifacts, phone numbers, and titles. This extensive NER functionality is essential for more complex relationship and event extraction tasks. The software finds applicability in numerous fields, including Business, Finance, Politics, Homeland Security, Law Enforcement, Military, National Security, and Social Media, making it a flexible option for organizations aiming for thorough textual insights. Additionally, its versatile nature allows users to tailor its usage to align with their specific analytical requirements, ensuring maximum effectiveness. As a result, NetOwl Extractor stands out as an indispensable tool for those engaged in comprehensive data analysis.
What is Lyncs?
A uniquely crafted contract data management system specifically designed for the financial services industry. Users can seamlessly upload files through drag-and-drop functionality, bulk uploads, or a dedicated API that securely integrates scans into the Lyncs platform. Moreover, entity reference data can be loaded to guarantee the accurate organization of scans throughout the system. The platform features automated duplicate detection, which combines machine learning with a rule-based hybrid auto-classification method to improve accuracy. Scans are organized by entity, type, and date, allowing for precise extraction of terms while taking amendment chains into account. To maximize precision and effectiveness, various techniques are utilized to automatically extract data from documents, merging machine learning, predefined rules, and user-assisted data capture. Each stage of the document processing is enhanced by a role-based workflow, enabling documents to be locked to prevent unauthorized changes, assigned to particular users, and moved through different workflow states via promotion or rejection. The system also boasts robust version tracking, auditing functionalities, and a data 'time-machine' feature that provides improved oversight and management. This comprehensive suite of features guarantees an exceptional level of control, accuracy, and efficiency in the realm of contract data management, supporting users in navigating complex regulatory environments.
Integrations Supported
ArcGIS
Elasticsearch
Google Maps
IBM Cloud
Kibana
MarkLogic
Palantir Apollo
SolrCommerce
Tableau
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided
Pricing Information
Pricing not provided
Supported Platforms
SaaS
Supported Platforms
SaaS
Customer Service / Support
Standard Support
Web-Based Support
Customer Service / Support
Web-Based Support
Training Options
Documentation Hub
On-Site Training
Training Options
Documentation Hub
Company Facts
Organization Name
NetOwl
Date Founded
1996
Company Location
United States
Company Website
www.netowl.com/entity-extraction
Company Facts
Organization Name
Logical Construct
Date Founded
2014
Company Location
United Kingdom
Company Website
www.logicalconstruct.com/lyncs-product-overview/
Categories and Features
Data Extraction
Not specified
Text Analytics
Not specified
Categories and Features
Contract Analysis
Not specified
Contract Management
Not specified