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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
Developing a topic model from the ground up requires a high level of programming skill. This specialized knowledge can be costly and often overshadows the essential understanding of the data itself. The process of manually labeling your training data is not only time-consuming but also labor-intensive and expensive. Outsourcing this task to low-wage workers may expedite the process and reduce costs, yet it often sacrifices both accuracy and detail. Each of these methods results in a static taxonomy that can be challenging to adapt over time. It's crucial to transition away from mere tagging and empower subject matter experts to engage with their data for modeling and analysis. With vast amounts of text data at your disposal, brimming with insights ready for exploration, the need for effective tools becomes clear. Pienso is here to assist with this challenge by enabling you to train models using your own data, as we recognize that this approach yields the best results. Regardless of whether your data is unstructured, semi-structured, lengthy, or concise, Pienso is equipped to help you transform it into valuable insights that can drive decision-making. By leveraging Pienso, you can unlock the full potential of your data without the traditional hurdles associated with topic modeling.
API Access
Has API
API Access
Has API
Integrations
AWS AI Services
AWS App Mesh
AWS Lambda
Amazon Comprehend Medical
Amazon Quick Suite
Amazon S3
Amazon Web Services (AWS)
Axon Ivy
Camunda
Datasaur
Integrations
AWS AI Services
AWS App Mesh
AWS Lambda
Amazon Comprehend Medical
Amazon Quick Suite
Amazon S3
Amazon Web Services (AWS)
Axon Ivy
Camunda
Datasaur
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
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
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/comprehend/
Vendor Details
Company Name
Pienso
Founded
2016
Country
United States
Website
www.pienso.com
Product 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
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
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Text Mining
Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering