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What is Omnisient?

We enable organizations to leverage the capabilities of first-party data collaboration while effectively reducing any potential risks involved. By transforming consumer data from a possible liability into a lucrative asset, companies can thrive in an evolving landscape that has surpassed traditional cookie usage. Our method promotes stronger partnerships with additional collaborators, which in turn amplifies value for clients. Additionally, we promote financial inclusion and enhance revenue through pioneering alliances that tap into alternative data resources. Our solution improves the precision of underwriting and increases profitability by integrating these varied data streams. Each participant utilizes our secure desktop application to anonymize, tokenize, and protect all personally identifiable information within their consumer data, ensuring it stays secure in their local setting. This process generates US-patented crypto-IDs for every anonymized consumer profile, facilitating the secure linking of shared consumers across multiple datasets within our neutral Cloud infrastructure. By employing our state-of-the-art technology, we are leading the charge in the next phase of consumer data management and collaboration. This guarantees that businesses can prosper in a data-centric future while adhering to the utmost standards of privacy and security, ultimately fostering greater trust and transparency in the marketplace.

What is AWS Clean Rooms?

Set up clean rooms in minutes and collaborate with your partners while safeguarding raw data privacy. AWS Clean Rooms enables users to quickly and easily create their own clean rooms without the hassle of building, managing, or maintaining custom solutions. Furthermore, companies can utilize APIs to smoothly integrate the features of AWS Clean Rooms into their current workflows. This service empowers organizations and their collaborators to effectively and safely analyze and work together on shared datasets without having to disclose or replicate each other’s sensitive information. With AWS Clean Rooms, users can rapidly construct a secure data clean room and work alongside any other AWS entity to discover valuable insights related to advertising techniques, investment decisions, and research projects. The platform simplifies the extraction of insights from multi-party data, ensuring that data movement is minimal while preserving the integrity of the foundational datasets. Ultimately, AWS Clean Rooms promotes a cooperative atmosphere while prioritizing data privacy and security at its foundation. By adopting this innovative service, businesses can enhance their collaborative efforts, driving better outcomes and more informed decisions.

Media

Media

Integrations Supported

Amazon QuickSight
Amazon Redshift
Amazon S3
Amazon SageMaker
Amazon Web Services (AWS)
Azure Machine Learning
Jupyter Notebook
Microsoft Power BI
Python

Integrations Supported

Amazon QuickSight
Amazon Redshift
Amazon S3
Amazon SageMaker
Amazon Web Services (AWS)
Azure Machine Learning
Jupyter Notebook
Microsoft Power BI
Python

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

Omnisient

Date Founded

2019

Company Location

South Africa

Company Website

omnisient.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/clean-rooms/

Categories and Features

Categories and Features

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