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Description
AWAI offers two distinct methods of operation, both leveraging the same analytical framework.
The first method, group analysis, eliminates the need for a traditional fixed questionnaire; instead, you can compose your questions in straightforward language and distribute an invite link, allowing respondents to participate without needing an account. Each individual engages with the AI independently, which prompts further discussion to elicit deeper insights. Once completed, the conversations are organized according to opinions, the underlying rationale, and the number of individuals who expressed each viewpoint, with unique opinions treated as outliers rather than being averaged out. This option accommodates up to 100 participants on a self-serve basis.
The second method involves real-time meetings where each participant selects their preferred language for communication and reading, and contributions are categorized under specific topics as the discussion unfolds. Following the meeting, the content is organized thematically rather than presented as a mere transcript.
Both approaches culminate in the creation of a document, where you can pose a straightforward question regarding the gathered information, resulting in a report that can be exported as a PDF and edited without any additional charges.
Additionally, a public demo is available, requiring no registration to access. This accessibility allows potential users to explore AWAI's capabilities effortlessly.
Description
Utilize natural language processing to derive insights from unstructured text without needing machine learning expertise, leveraging a suite of features from Cognitive Service for Language. Enhance your comprehension of customer sentiments through sentiment analysis and pinpoint significant phrases and entities, including individuals, locations, and organizations, to identify prevalent themes and trends. Categorize medical terminology with specialized, pretrained models tailored for specific domains. Assess text in numerous languages and uncover vital concepts within the content, such as key phrases and named entities encompassing people, events, and organizations. Investigate customer feedback regarding your brand while analyzing sentiments related to particular subjects through opinion mining. Moreover, extract valuable insights from unstructured clinical documents like doctors' notes, electronic health records, and patient intake forms by employing text analytics designed for healthcare applications, ultimately improving patient care and decision-making processes.
API Access
Has API
API Access
Has API
Screenshots View All
No images available
Integrations
Azure Marketplace
TAS Insight Engine
Unremot
Pricing Details
$11.99/month
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
OFFICE KAMIYA Inc.
Founded
2016
Country
Japan
Website
www.officekamiya.co.jp/
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
azure.microsoft.com/en-us/services/cognitive-services/text-analytics/
Product Features
Qualitative Data Analysis
Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis
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
Alternatives
No Alternatives