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features
design
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What is PAVE?

PAVE allows individuals to transform their PDF documents into accessible formats, ensuring they are compatible with widely-used reading software while maintaining the original design. This service is available at no cost for personal use, enabling automatic adjustments directly through the platform. Additionally, users have the option to manually apply further recommended modifications to improve accessibility. The files will be stored on PAVE's server for a maximum of three weeks unless the user decides to delete them sooner. While PAVE aims for precision, there is a chance that the processing could lead to changes in the document's content or visual presentation, so it is crucial for users to review the final output carefully. The ZHAW organization distances itself from any responsibility for such modifications. Previously, the ICT accessibility lab had created plugins to convert Microsoft Word and PowerPoint files into accessible PDFs, but they fell short in addressing the accessibility of already existing PDFs—a gap that PAVE successfully fills, thus offering a thorough solution. This advancement empowers users to easily and effectively improve the accessibility of documents they have created in the past, enhancing their overall usability for all readers. Consequently, PAVE represents a significant step forward in making digital content more inclusive.

What is Indyco?

Start your top-down evaluation by gaining an extensive overview of a sample Data Platform, which will enable you to explore various domains and reveal their interconnections with different organizational data. The transformation of a supply chain's business model and the application of Enterprise Data Platform strategies in a banking environment are just a few examples that highlight the practical benefits of using Indyco as a data modeling tool. This initiative notably enhanced the data culture within a leading entity in Italy's food and agriculture industry, paving the way for self-service reporting capabilities. Business users actively engaged with the Conceptual Model presented on a large display, working alongside IT teams during collaborative design sessions aimed at refining their Data Platform. Furthermore, a bank effectively established best practices in Data Platform design by leveraging Indyco, incorporating aspects such as conceptual modeling, automated documentation, and the formulation of a business glossary. Consequently, the amalgamation of these practices not only optimized operations but also nurtured a conducive atmosphere for data-driven decision-making, ultimately leading to transformative outcomes across the organization. The commitment to data excellence became a cornerstone of their strategic initiatives, fostering innovation and responsiveness in a rapidly changing market landscape.

Media

Media

Integrations Supported

Microsoft PowerPoint
Microsoft Word
Totality

Integrations Supported

Microsoft PowerPoint
Microsoft Word
Totality

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
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

PAVE

Date Founded

2014

Company Location

Germany

Company Website

pave-pdf.org

Company Facts

Organization Name

Indyco

Date Founded

2013

Company Location

Italy

Company Website

www.indyco.com

Categories and Features

Categories and Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

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