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Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

AKIN represents an innovative data analytics platform that leverages cutting-edge Artificial Intelligence Software. It eliminates the need for costly and time-intensive preliminary tasks associated with Natural Language Processing, enabling users to swiftly implement a practical solution that delivers both accuracy and effectiveness. There is no requirement for a team of specialists to undertake the intricate work of feature engineering, the selection of machine learning algorithms, or extensive testing of various methods, including tagging large datasets and training machine learning models. With AKIN AI, users can easily configure or add the concepts they wish to identify, allowing the platform to utilize this input alongside its inherent knowledge to accurately detect those concepts. In doing so, it provides valuable insights and conclusions with remarkable precision, streamlining the analytical process significantly. Ultimately, AKIN empowers users to harness the power of AI without the barriers typically associated with advanced data analytics.

Description

At Iris.ai we have spent the last 6 years building an award-winning AI engine for scientific text understanding. Our algorithms for text similarity, tabular data extraction, domain-specific entity representation learning and entity disambiguation and linking measure up to the best in the world. On top of that, our machine builds a comprehensive knowledge graph containing all entities and their linkages to allow humans to learn from it, use it and also give feedback to the system. The Iris.ai Researcher Workspace is a flexible tool suite that allows to approach a project in a variety of ways. Modules include content based explorative search, machine analysis of document sets, extracting and systematizing data points, automatically writing summaries of multiple documents - and very powerful filters based on context descriptions, the machine’s analysis, or specific data points or entities. The Iris.ai engine for scientific text understanding is a powerful interdisciplinary system that can be automatically reinforced on a specific research field for much more nuanced machine understanding - without human training or annotation.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

$129.99/one-time/user
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

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

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 No 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Grapple Data Technology

Founded

2012

Country

United States

Website

www.grappledata.com/default.aspx

Vendor Details

Company Name

Iris.ai

Founded

2015

Country

Norway

Website

iris.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 

Product Features

Data Extraction

Disparate Data Collection No 
Document Extraction No 
Email Address Extraction No 
IP Address Extraction No 
Image Extraction No 
Phone Number Extraction No 
Pricing Extraction No 
Web Data Extraction No 

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 

Qualitative Data Analysis

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

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