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Description
Amazon Comprehend is an innovative natural language processing (NLP) tool that employs machine learning techniques to extract valuable insights and connections from text without requiring any prior machine learning knowledge.
Your unstructured data holds a wealth of possibilities, with sources like customer emails, support tickets, product reviews, social media posts, and even advertising content offering critical insights into customer sentiments that can drive your business forward. The challenge lies in how to effectively tap into this rich resource. Fortunately, machine learning excels at pinpointing specific items of interest within extensive text datasets—such as identifying company names in analyst reports—and can also discern the underlying sentiments in language, whether that involves recognizing negative reviews or acknowledging positive interactions with customer service representatives, all at an impressive scale.
By leveraging Amazon Comprehend, you can harness the power of machine learning to reveal the insights and relationships embedded within your unstructured data, empowering your organization to make more informed decisions.
Description
Industry experts indicate that unstructured data stands as the most significant source of untapped and undervalued customer information, and its growth is accelerating in today's customer-focused landscape. In an age characterized by Big Data, where corporate data doubles approximately every three months, effectively leveraging this information has become essential for maintaining a competitive edge and ensuring business longevity. EpiAnalytics offers Artificial Intelligence (AI) solutions tailored to meet your business requirements, enabling you to extract greater value from the data you already possess, no matter where it is stored. Our solutions aim to boost sales, enhance data quality, guarantee compliance, and improve operational efficiencies. By integrating our legacy VINoptions product with its AI and VIN data engineering capabilities and our extensive ChromeData vehicle data catalog that spans 30 years, we have developed an advanced VIN decoding solution. Additionally, ChromeData VIN Descriptions have become the industry benchmark for accurately identifying and detailing vehicles based on their VIN. This innovative approach not only streamlines processes but also empowers businesses to make data-driven decisions with confidence.
API Access
Has API
Yes
API Access
Has API
No
Integrations
AWS AI Services
Yes
AWS App Mesh
Yes
AWS Lambda
Yes
Amazon Comprehend Medical
Yes
Amazon Quick Suite
Yes
Amazon S3
Yes
Amazon Web Services (AWS)
Yes
Axon Ivy
Yes
Camunda
Yes
Datasaur
Yes
Integrations
AWS AI Services
No
AWS App Mesh
No
AWS Lambda
No
Amazon Comprehend Medical
No
Amazon Quick Suite
No
Amazon S3
No
Amazon Web Services (AWS)
No
Axon Ivy
No
Camunda
No
Datasaur
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
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
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
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
No
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/comprehend/
Vendor Details
Company Name
J.D. Power
Founded
1968
Country
United States
Website
www.jdpower.com/business/epianalytics
Product Features
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
No
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
No
Sentence Segmentation
No
Stemming/Lemmatization
No
Tokenization
No
Text Mining
Boolean Queries
No
Document Filtering
No
Graphical Data Presentation
No
Language Detection
No
Predictive Modeling
No
Sentiment Analysis
No
Summarization
No
Tagging
No
Taxonomy Classification
No
Text Analysis
No
Topic Clustering
No
Product Features
Conversational AI
Code-free Development
No
Contextual Guidance
No
For Developers
No
Intent Recognition
No
Multi-Languages
No
Omni-Channel
No
On-Screen Chats
No
Pre-configured Bot
No
Reusable Components
No
Sentiment Analysis
No
Speech Recognition
No
Speech Synthesis
No
Virtual Assistant
No
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
No
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
No
Sentence Segmentation
No
Stemming/Lemmatization
No
Tokenization
No