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What is Komprehend?

Komprehend AI provides a comprehensive suite of document classification and natural language processing (NLP) APIs tailored for software developers. Utilizing sophisticated NLP models trained on an extensive collection of over a billion documents, we achieve exceptional accuracy across a wide array of common NLP tasks, such as sentiment analysis and emotion detection. You can try our free demo today to see how our Text Analysis API performs in practice, consistently offering high precision when extracting meaningful insights from unstructured text data. Suitable for diverse sectors, including finance and healthcare, our solutions also facilitate private cloud setups through Docker containers or can be deployed on-premise, ensuring your data's confidentiality. We strictly adhere to GDPR compliance standards, emphasizing the safeguarding of your sensitive information. By monitoring online conversations, you can gain a deeper understanding of the social sentiment related to your brand, product, or service. Sentiment analysis involves a detailed contextual review of text to uncover and extract subjective insights, thereby enriching your comprehension of audience opinions. Furthermore, our tools are designed for easy integration into current workflows, simplifying the process for developers to leverage the capabilities of NLP. With these advanced features, Komprehend AI empowers businesses to make data-driven decisions by providing clarity on public sentiment.

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

Unremot
Azure Marketplace
Docker
Quickwork
TAS Insight Engine

Integrations Supported

Unremot
Azure Marketplace
Docker
Quickwork
TAS Insight Engine

API Availability

Has API

API Availability

Has API

Pricing Information

$79 per month
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

Komprehend

Company Location

India

Company Website

komprehend.io

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

Emotion Recognition

Facial Emotions
Facial Expression Analysis
Machine Learning
Photo Emotions
Speech Emotions
Video Emotions
Written Text Emotions

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

Text Mining

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

Categories and Features

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

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