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Average Ratings 0 Ratings
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.
Description
Scientific Figure is an online AI platform that enables users to produce and modify scientific graphics based on text descriptions, drawings, abstracts, or PDF documents of research papers. It features a variety of generators for creating scientific illustrations, visual abstracts, research posters, graphs, and diagrams, including PRISMA flowcharts, circuit diagrams, and phylogenetic trees. Users can refine and manipulate figure components within an editing interface, allowing them to modify labels and colors before exporting their creations in formats such as PNG, JPG, layered SVG, or editable PowerPoint files. The tool accommodates a range of illustration styles and facilitates plot generation from inputted data or uploaded files. Tailored for researchers, educators, principal investigators, and science communicators, it aids in the preparation of materials for publication, presentations, and educational purposes. A complimentary plan provides 100 credits, while paid subscriptions offer increased credit limits, additional export formats, and a certificate for publication licensing, making it a versatile choice for anyone in the scientific field. This flexibility ensures a broad spectrum of users can effectively visualize their data and enhance their communication of scientific concepts.
API Access
Has API
No
API Access
Has API
No
Screenshots View All
No images available
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$9.90/month
Lite costs $9.90/month or $99/year ($8.25/month equivalent when billed yearly; two months free). Pro costs $19/month or $144/year. Plus costs $39/month or $240/year. The Free plan includes 100 credits and requires no card.
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
No
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
No
Webinars
Yes
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
Iris.ai
Founded
2015
Country
Norway
Website
iris.ai/
Vendor Details
Company Name
John Barrett
Website
scientificfigure.com
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