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What is Gavagai?

Our cutting-edge natural language processing technology utilizes artificial intelligence to gather, examine, and present insights from various types of customer communications. This encompasses everything from call transcripts, chat logs, emails, support inquiries, return requests, social media engagements, to surveys, all available in 47 languages. With our Explorer tool, users can swiftly evaluate open-ended text feedback within mere minutes. Furthermore, Explorer is equipped with an API that facilitates the effortless integration of unstructured text data into your business intelligence frameworks. The domain of employee experience is centered on evaluating and pinpointing the factors that enhance employee satisfaction and drive motivation. Our solutions enable organizations to effectively manage, analyze, and interpret large volumes of unstructured natural language information in significantly less time than typical methods. Designed for ease of use, the platform allows you to develop custom bots that cater to your unique business needs without requiring any programming skills. Immediate enhancements in operational efficiency can be realized just minutes after setup. In addition, the Gavagai API offers a comprehensive set of semantic analysis tools supporting 47 languages, granting users instant access to intuitive endpoints. This powerful functionality ensures that organizations can capitalize on insights drawn from their data, thereby improving their decision-making processes and fostering a more engaged workforce. Ultimately, by leveraging these advanced technologies, businesses can not only enhance customer communication but also significantly boost overall productivity and employee engagement.

What is Amazon Comprehend?

Amazon Comprehend is an advanced natural language processing (NLP) platform that utilizes machine learning techniques to uncover insights and identify relationships within textual data, requiring no previous machine learning expertise for its application. Your unstructured data, which may originate from customer emails, support requests, product reviews, social media conversations, or marketing materials, is rich with insights that can greatly benefit your organization by reflecting customer attitudes. The main challenge is to harness this abundant information, but machine learning is adept at extracting specific elements from large volumes of text, such as identifying company names in financial reports, along with gauging the sentiment conveyed in the language, whether it involves addressing negative feedback or recognizing positive experiences with customer service. Amazon Comprehend enables you to uncover these hidden insights and relationships in your unstructured data, serving as a vital tool for improving business strategies and making informed decisions. As a result, leveraging this technology can transform the way you understand and respond to customer needs, ultimately driving growth and innovation within your organization.

Media

Media

Integrations Supported

AWS AI Services
AWS App Mesh
AWS Lambda
Amazon Comprehend Medical
Amazon Quick Suite
Amazon S3
Amazon Web Services (AWS)
Axon Ivy
Camunda
Datasaur
FormKiQ
Mantium
PubNub
Qlik Staige
Quickwork
SurveyMonkey Enterprise
iText
n8n

Integrations Supported

AWS AI Services
AWS App Mesh
AWS Lambda
Amazon Comprehend Medical
Amazon Quick Suite
Amazon S3
Amazon Web Services (AWS)
Axon Ivy
Camunda
Datasaur
FormKiQ
Mantium
PubNub
Qlik Staige
Quickwork
SurveyMonkey Enterprise
iText
n8n

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
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

Gavagai

Date Founded

2009

Company Location

Sweden

Company Website

www.gavagai.io

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/comprehend/

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

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

Text Mining

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

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