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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

Tisane API is an NLU API that focuses on law enforcement and abusive content. Tisane detects: • hate speech • Cyberbullying • Criminal activity • Sexual advances • Attempts to establish external contact More. Tisane identifies the issue and pinpoints the text fragment that is infringing. Optionally, an explanation can be provided for audit or sanity checks. Tisane can handle 30 languages, even if it contains slang or obfuscation.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

PubNub 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 
FormKiQ Yes 
Maltego No 
Mantium Yes 
Qlik Staige Yes 
Quickwork Yes 
Slack No 
Zapier No 
Zendesk Sunshine No 
iText Yes 
n8n Yes 

Integrations

PubNub Yes 
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 
FormKiQ No 
Maltego Yes 
Mantium No 
Qlik Staige No 
Quickwork No 
Slack Yes 
Zapier Yes 
Zendesk Sunshine Yes 
iText No 
n8n No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Subscription SaaS or on prem
Free Trial No 
Free Version Yes 

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 Yes 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
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

Tisane Labs

Founded

2017

Country

Singapore

Website

tisane.ai

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

Content Moderation

Artificial Intelligence No 
Audio Moderation No 
Brand Moderation No 
Comment Moderation No 
Customizable Filters No 
Image Moderation No 
Moderation by Humans No 
Reporting / Analytics No 
Social Media Moderation No 
User-Generated Content (UGC) Moderation No 
Video Moderation No 

Natural Language Processing

Co-Reference Resolution Yes 
In-Database Text Analytics No 
Named Entity Recognition No 
Natural Language Generation (NLG) No 
Open Source Integrations No 
Parsing Yes 
Part-of-Speech Tagging Yes 
Sentence Segmentation Yes 
Stemming/Lemmatization Yes 
Tokenization Yes 

Qualitative Data Analysis

Annotations Yes 
Collaboration No 
Data Visualization No 
Media Analytics No 
Mixed Methods Research No 
Multi-Language Yes 
Qualitative Comparative Analysis No 
Quantitative Content Analysis No 
Sentiment Analysis Yes 
Statistical Analysis No 
Text Analytics Yes 
User Research Analysis No 

Text Mining

Boolean Queries No 
Document Filtering No 
Graphical Data Presentation No 
Language Detection Yes 
Predictive Modeling No 
Sentiment Analysis Yes 
Summarization No 
Tagging Yes 
Taxonomy Classification Yes 
Text Analysis Yes 
Topic Clustering Yes 

Alternatives

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