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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 Google Cloud Natural Language API?

Employ cutting-edge machine learning methodologies for an in-depth analysis of text that facilitates the extraction, interpretation, and secure storage of textual information. Utilizing AutoML, one can effortlessly build high-performance custom machine learning models without needing to write any code. Enhance your applications by implementing natural language understanding via the Natural Language API, which significantly boosts their capabilities. By employing entity analysis, you can accurately identify and categorize various elements in documents such as emails, chats, and social media exchanges, followed by conducting sentiment analysis to assess customer feedback and generate actionable insights for enhancing products and user experiences. Moreover, the Natural Language API, paired with speech-to-text functionalities, allows you to gather meaningful insights from audio sources as well. The Vision API also adds to your toolkit by providing optical character recognition (OCR) to convert scanned documents into digital formats. Additionally, the Translation API broadens your understanding of sentiment across multiple languages, making it easier to connect with diverse audiences. With the ability to perform custom entity extraction, you can uncover specialized entities within your documents that might be overlooked by conventional models, thereby saving time and resources that would otherwise be spent on manual processing. Furthermore, this robust methodology allows you to train your own high-quality machine learning models, enabling precise classification, extraction, and sentiment assessment, which enhances the efficiency and focus of your analysis. Ultimately, this all-encompassing strategy guarantees a thorough understanding of both textual and audio data, equipping businesses with profound insights to drive better decision-making and strategies.

Media

Media

Integrations Supported

.NET
C
C#
Gemini
Gemini 1.5 Flash
Gemini 2.0
Gemini 2.0 Flash
Gemini Advanced
Gemini Nano
Google Cloud AutoML
Google Cloud Platform
Google Cloud Speech-to-Text
Google Cloud Vision AI
Hyland RPA
Java
PubNub
Python
Unremot
Vertex AI
n8n

Integrations Supported

.NET
C
C#
Gemini
Gemini 1.5 Flash
Gemini 2.0
Gemini 2.0 Flash
Gemini Advanced
Gemini Nano
Google Cloud AutoML
Google Cloud Platform
Google Cloud Speech-to-Text
Google Cloud Vision AI
Hyland RPA
Java
PubNub
Python
Unremot
Vertex AI
n8n

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Hyland Software

Date Founded

1991

Company Location

United States

Company Website

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

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

cloud.google.com/natural-language

Categories and Features

Document Management

Access Controls
Archiving & Retention
Collaboration Tools
Compliance Tracking
Document Archiving
Document Assembly
Document Capture
Document Conversion
Document Delivery
Document Indexing
Document Retention
Electronic Signature
Email Management
File Recovery
File Type Conversion
Forms Management
Full Text Search
Offline Access
Optical Character Recognition
Print Management
Version Control

Categories and Features

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Natural Language Generation

Business Intelligence
CRM Data Analysis and Reports
Chatbot
Email Marketing
Financial Reporting
Multiple Language Support
SEO
Web Content

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

Qualitative Data Analysis

Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis

Text Mining

Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering

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