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Description
Komprehend AI offers an extensive range of document classification and NLP APIs designed specifically for software developers. Our advanced NLP models leverage a vast dataset of over a billion documents, achieving top-notch accuracy in various common NLP applications, including sentiment analysis and emotion detection. Explore our free demo today to experience the effectiveness of our Text Analysis API firsthand. It consistently delivers high accuracy in real-world scenarios, extracting valuable insights from open-ended text data. Compatible with a wide range of industries, from finance to healthcare, it also supports private cloud implementations using Docker containers or on-premise deployments, ensuring your data remains secure. By adhering to GDPR compliance guidelines meticulously, we prioritize the protection of your information. Gain insights into the social sentiment surrounding your brand, product, or service by actively monitoring online discussions. Sentiment analysis involves the contextual examination of text to identify and extract subjective insights from the material, thereby enhancing your understanding of audience perceptions. Additionally, our tools allow for seamless integration into existing workflows, making it easier for developers to harness the power of NLP.
Description
At the crossroads of Customer Experience and Business Intelligence lies Customer Intelligence, which uncovers the vital link between customer sentiments and the performance metrics that influence business outcomes. With Explore, you can harness the insights necessary for your organization to make significant and informed decisions. Your collection of customer opinions and emotions captured through feedback, surveys, and support interactions can be effectively utilized in OdinExplore for broader analysis. By investigating the themes present in customer feedback, you can identify which topics resonate most with your audience. Explore offers features like auto-terms, the creation of key topics, dictionary applications, and emotional sentiment analysis. You can also segment your data by various demographics, ratings, or timeframes to reveal the differences among customer groups. Running multiple experiments allows you to uncover fresh insights about diverse customer segments, products, and more, ultimately leading to more tailored business strategies. This comprehensive approach not only enhances understanding but also drives continuous improvement in customer engagement.
API Access
Has API
API Access
Has API
Integrations
Docker
Quickwork
Unremot
Pricing Details
$79 per month
Free Trial
Free Version
Pricing Details
$999 per month
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
Komprehend
Country
India
Website
komprehend.io
Vendor Details
Company Name
OdinAnswers
Country
United States
Website
odinanswers.com/platform/
Product 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
Product Features
Text Mining
Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering