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What is curios.IT?

curios.IT is an intuitive software solution designed for the exploration, mining, and visualization of 3D data, accessible via various web browsers, Windows 10, and devices like the iPad. It allows users to adeptly identify patterns, relationships, and structures in their datasets with ease. This tool enhances visual data mining capabilities, facilitating thorough analyses of diverse multivariate data while enabling the simultaneous visualization of as many as 13 different variables. Its effectiveness shines especially when analyzing financial records, transaction histories, or customer data, making it a highly adaptable resource for data analysts. By streamlining the process of data interpretation, curios.IT helps users derive valuable insights without unnecessary complexity, ultimately enhancing their analytical capabilities and decision-making processes.

What is Gist?

Elevate your structured data by transforming it into engaging microsites that create connections and promote interaction, enabling insights to be examined and shared seamlessly with both internal teams and external audiences. The interfaces are designed to be intuitive, making it easy for users to navigate through structured data effortlessly. Enhance the effectiveness of your reports and articles by incorporating striking visualizations, which can significantly amplify the impact of your analysis. Teams are equipped to publish, update, and collaborate on these visualizations smoothly, utilizing shared annotations to facilitate clearer communication. By developing interactive galleries and data visualization platforms, you can gain a deeper understanding of the breadth and intricacies of your collections. Strengthening your ties with both internal groups and external audiences becomes possible through the provision of context via user insights and pertinent articles. Dynamic and fluid visualizations will animate your data, transforming it into compelling narratives that resonate with viewers. Distributing eye-catching visualizations online can ignite interest and motivate your audience to engage actively. By embedding these visualizations on your website, you not only encourage dialogue through user annotations but also cultivate a vibrant community around your data. Gist serves as the go-to tool for these purposes, being offered as open-source software under the GNU General Public License, which nurtures collaborative development and innovation. This approach significantly boosts accessibility and empowers users to make their contributions by creating their own enhancements and adaptations. Ultimately, fostering a culture of collaboration around data visualization can yield richer insights and stronger engagement.

Media

Media

Integrations Supported

Google Sheets
Mailifier

Integrations Supported

Google Sheets
Mailifier

API Availability

Has API

API Availability

Has API

Pricing Information

$5.00/one-time/user
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

Kanohi

Date Founded

2009

Company Location

Switzerland

Company Website

kanohi.ch/

Company Facts

Organization Name

Gist Software

Company Location

India

Company Website

www.gistapp.com

Categories and Features

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

Categories and Features

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

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