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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

The insurance sector focuses on achieving optimal rates and effectively managing risk. In such a competitive landscape, reducing manual processes is essential to distinguish ourselves from other industry players. A significant workforce is often necessary to sift through, interpret, categorize, analyze, and disseminate information for underwriting and support activities. Much of this information is unstructured and text-based, requiring manual examination. Scaling operations typically involves hiring additional personnel or resorting to outsourcing solutions. It is vital to filter and classify complaints based on their subject matter and severity level. Automotive businesses collect these complaints through various channels, including emails, feedback forms, and comments. Lymba’s Underwriting and Support NLP solution addresses the text-heavy challenges by converting data into actionable insights; this efficiency not only saves time and resources but also facilitates the initial review process, ultimately enhancing overall productivity and decision-making. By leveraging such technology, companies can focus more on strategic initiatives rather than getting bogged down by manual data handling.

Description

The simplest method for pulling data points from unstructured text involves simultaneously scanning research documents, prospectuses, and customer feedback to identify, track, and assess significant, user-defined data metrics. You can access over 100 distinct data points to enhance your investment and risk management strategies effectively. By searching and assembling customized datasets from EDGAR and various public or private resources, you can optimize your deal underwriting process. Additionally, this approach can streamline the legal workflows within capital markets and structured finance. Instantly retrieve over 100 data points to help categorize, compare, and collaborate with your clients more effectively. Deconstructing unstructured text from sources like PubMed and clinical trial data allows you to break down information into categories such as diseases, genes, proteins, and symptoms, ensuring that all your research is consolidated in one location. You can incorporate research from any source into your workspaces effortlessly with our convenient Chrome plug-in, which also enables the transformation of digital PDFs into machine-readable formats. Furthermore, you will receive outputs in JSON and HTML formats that include a detailed section hierarchy, as well as the removal of watermarks, multi-level tables, lists, headers, and footers, making your data more accessible and manageable than ever before. This comprehensive solution not only simplifies data extraction but also enhances your overall analytical capabilities.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Google Chrome

Integrations

Google Chrome

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

Lymba

Founded

2005

Country

United States

Website

www.lymba.com

Vendor Details

Company Name

NLMatics

Founded

2019

Country

United States

Website

www.nlmatics.com

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

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

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

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