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What is GetReal?

GetReal Security offers advanced, enterprise-grade solutions for content verification that specifically target deepfakes and impersonation risks in real time across a range of audio and video platforms, including collaborative tools. Their extensive, multi-faceted defense approach includes various analyses such as content credentials, pixel integrity, physical attributes, provenance, semantic context, human signals, biometric data, behavioral patterns, and environmental factors to ensure strong protection. Designed for seamless integration with existing collaboration and cybersecurity systems, GetReal Security enables organizations to maintain trust in digital communications by verifying the authenticity, origin, and integrity of content, effectively addressing the challenges posed by AI-generated misinformation and harmful digital assets. In addition, their cutting-edge technology not only protects against existing threats but also evolves to meet new challenges in the ever-changing digital landscape, ensuring long-term resilience against digital deception. This commitment to innovation reinforces their role as a leader in the fight against the misuse of technology in communication.

What is FakeCatcher?

Intel has introduced the innovative FakeCatcher technology for deepfake detection, which analyzes the "blood flow" within video pixels to swiftly determine the authenticity of videos in just milliseconds. This cutting-edge system is integrated into popular editing software that content creators and broadcasters regularly use, facilitating the identification of altered content during the editing phase. Additionally, it plays a vital role in vetting user-generated content, ensuring that authenticity verification is an integral part of the upload process. By making deepfake detection universally accessible, it empowers both individuals and organizations to effortlessly confirm the legitimacy of videos. Deepfakes, which constitute synthetic media that misrepresent reality by fabricating actors and actions, pose a significant challenge in today’s digital landscape. While numerous deep learning detection systems focus on analyzing raw data for inconsistencies, FakeCatcher adopts a unique method by identifying genuine markers of authenticity in real footage, emphasizing the subtle evidence of human characteristics, like the slight changes in pixel color due to blood flow. As the heart pumps, the color of our veins changes, generating the distinct data that FakeCatcher leverages to differentiate between authentic and doctored videos. This groundbreaking detection technology marks a substantial advancement in the ongoing battle against the misuse of deepfake technology, providing a beacon of hope in preserving the integrity of visual media. As the prevalence of deepfakes continues to rise, the implementation of such innovative solutions will be essential in safeguarding truth in digital content.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

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

GetReal

Company Location

United States

Company Website

www.getrealsecurity.com

Company Facts

Organization Name

Intel

Company Location

United States

Company Website

www.intel.com/content/www/us/en/newsroom/news/intel-introduces-real-time-deepfake-detector.html#gs.08lxwl

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