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What is Hyland Document Filters?

Discover what firms like Cisco, Reveal Data, and Absolute Software have learned about Catalyst and similar products! Document Filters serves as an essential toolkit for facilitating file inspection and processing capabilities within applications for eDiscovery, data loss prevention, text analysis, and content management. It empowers users to search through, archive, and retrieve files efficiently. Are your users overwhelmed by the variety of file formats and the sheer volume of documents? We delve into how Document Filters enhances efficiency and delivers customer value, significantly benefiting all users in the process. Furthermore, Document Filters enables software developers to embed top-tier file identification features into their applications. By utilizing intelligent file identification, Document Filters effectively analyzes source content without solely depending on the filename extension, ensuring more accurate processing. This innovative approach not only streamlines workflows but also elevates the overall user experience.

What is Azure Text Analytics?

Harness natural language processing to gain valuable insights from unstructured text without requiring any machine learning knowledge, by utilizing an array of features from the Cognitive Services for Language. Elevate your understanding of customer emotions through sentiment analysis and identify key phrases and entities such as people, places, and organizations to uncover common themes and patterns. Use specialized, pretrained models to classify medical terminology specific to various fields. Evaluate text across multiple languages and reveal essential concepts within the content, which include key phrases and named entities that highlight individuals, events, and organizations. Delve into customer feedback regarding your brand while examining sentiments linked to specific topics through opinion mining techniques. Additionally, derive critical insights from unstructured clinical documents, including doctors' notes, electronic health records, and patient intake forms, by applying text analytics tailored for healthcare settings, ultimately enhancing patient care and informing decision-making processes. By integrating these advanced capabilities, organizations can stay ahead of trends and better meet the needs of their stakeholders.

Media

Media

Integrations Supported

.NET
C
C#
C++
Hyland RPA
Java
Python

Integrations Supported

Azure Marketplace
TAS Insight Engine
Unremot

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Hyland

Date Founded

1991

Company Location

United States

Company Website

www.hyland.com/en/solutions/products/document-filters

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/services/cognitive-services/text-analytics/

Categories and Features

Document Management

Archiving & Retention
Document Archiving

Text Analytics

Not specified

Categories and Features

Natural Language Processing

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

Sentiment Analysis

Not specified

Text Analytics

Not specified

Popular Alternatives

Popular Alternatives

Google Cloud Natural Language API Reviews & Ratings

Google Cloud Natural Language API

Google
5.0 out of 5 stars