Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
The TextRazor API provides an efficient and precise means of uncovering the Who, What, Why, and How within your news articles. It features capabilities such as Entity Extraction, Disambiguation, and Linking, alongside Keyphrase Extraction, Automatic Topic Tagging, and Classification, supporting twelve different languages. This tool performs an in-depth analysis of your content, allowing for the extraction of Relations, Typed Dependencies between terms, and Synonyms, which empowers the development of advanced semantic applications that are context-aware. Furthermore, it enables the swift extraction of custom entities like products and companies, allowing users to create specific rules for tagging their content with personalized categories. TextRazor comprises a versatile text analysis infrastructure that can be utilized either via the cloud or through self-hosting. By integrating cutting-edge natural language processing techniques with an extensive repository of factual information, TextRazor aids in quickly deriving valuable insights from your documents, tweets, or web pages, making it an indispensable tool for content creators and analysts alike. This comprehensive approach ensures that users can maximize the effectiveness of their data processing and analysis efforts.
API Access
Has API
API Access
Has API
Screenshots View All
No images available
Integrations
Fleece AI
Neota
OpenResty
Pipedream
TIMi
Pricing Details
$11.99/month
Free Trial
Free Version
Pricing Details
$200 per month
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
TextRazor
Founded
2011
Country
United Kingdom
Website
www.textrazor.com
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
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
Text Mining
Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering
Alternatives
No Alternatives