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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.
Description
The PDFix SDK empowers users to automatically enhance the accessibility of existing PDF documents. It facilitates the conversion of standard PDFs into high-quality, accessible PDF/UA formats. With its auto-tagging capability, the SDK identifies crucial document elements such as text, images, tables, headers and footers, headings, lists, and reading order. By enabling automated batch processing, it not only saves valuable time but also significantly lowers remediation expenses. If you've ever attempted to extract information from multiple PDF files, you certainly understand the challenges involved. Utilizing advanced machine learning techniques, the SDK has developed an algorithm that enables seamless and structured data extraction. As a result, users can easily identify various logical components, including text, headings, images, tables, headers and footers, and lists. Furthermore, it allows for scraping data from PDFs and converting it into your preferred formats, such as HTML, CSV, JSON, or XML, making the process much more efficient and user-friendly. This functionality is particularly beneficial for organizations aiming to improve their document accessibility and streamline data management.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Google Chrome
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
$490 per year
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
Yes
iPad App
Yes
Android App
Yes
Windows
Yes
Mac
Yes
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
Yes
Vendor Details
Company Name
NLMatics
Founded
2019
Country
United States
Website
www.nlmatics.com
Vendor Details
Company Name
PDFix
Country
Slovakia
Website
pdfix.net
Product Features
Data Extraction
Disparate Data Collection
No
Document Extraction
No
Email Address Extraction
No
IP Address Extraction
No
Image Extraction
No
Phone Number Extraction
No
Pricing Extraction
No
Web Data Extraction
No
Product Features
Annotations
Yes
Convert to PDF
No
Digital Signature
Yes
Encryption
No
Merge / Append
Yes
PDF Reader
Yes
Watermarking
Yes
