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What is Frame?

Frame introduces a revolutionary method for enhancing security awareness, aimed at safeguarding organizations from AI-related dangers by gaining insights into their unique circumstances and offering customized security training, simulations, and deepfake scenarios within minutes. Unlike conventional awareness programs that rely on generic resources, Frame develops training initiatives and simulations tailored to your organization's specific environment, which encompasses the threats it encounters, its policies, employee roles, technological framework, and genuine organizational context. This cutting-edge platform equips employees to tackle a diverse range of challenges, going beyond simple phishing to provide personalized instruction on identifying deepfakes, recognizing AI-driven social engineering tactics, secure coding methods, advanced security threats, compliance matters, privacy issues, developer training, and the latest security updates pertinent to your sector. The simulations created by Frame are exceptionally lifelike, crafted using details pertinent to your organization, resulting in authentic phishing emails, voice communications, and deepfake videos, all engineered with varying difficulty levels that cater to each employee's abilities. Moreover, Frame utilizes comprehensive multichannel campaigns that effectively replicate the strategies employed by real-world attackers, ensuring that your team is well-prepared for the constantly changing landscape of cybersecurity risks. By combining these elements, Frame not only enhances individual security awareness but also fosters a culture of proactive security within the organization.

What is Clarity?

Detecting deepfakes in real-time and on a large scale is essential for both current safety and future security. These digital fabrications pose a significant threat as they undermine trust within society and among individuals, evolving constantly to evade recognition. Their widespread availability means they can be easily created, posing a danger across various digital platforms. Such manipulations can affect all types of digital media, including videos, audio recordings, and images, enabling them to impersonate almost anyone convincingly. Tackling the challenge of deepfake detection requires sustained and sophisticated research in the realms of artificial intelligence and cybersecurity. Leading experts in the field are collaborating with specialists to develop advanced technologies that confront this issue head-on. Clarity emerges as a groundbreaking AI cybersecurity startup focused on combating deepfakes alongside the rising threats of social engineering and phishing, driven by the rapid advancement of generative AI. With its innovative and patent-pending technology, Clarity effectively identifies alterations in videos, images, and audio, while maintaining media authenticity through secure watermarking practices. As generative AI continues its rapid evolution, the need for effective and innovative detection strategies becomes increasingly critical, emphasizing the importance of ongoing research and development in this area. The future of digital content integrity hinges on our ability to stay one step ahead of these emerging threats.

Media

Media

Integrations Supported

Gmail
Google Cloud Platform
Microsoft 365
Microsoft Outlook
Microsoft Teams
Slack

Integrations Supported

SAP Store
graphis

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Frame

Company Location

United States

Company Website

framesecurity.com

Company Facts

Organization Name

Clarity

Company Location

Israel

Company Website

www.getclarity.ai/

Categories and Features

Categories and Features

AI Cybersecurity

Not specified

Deepfake Detection

Not specified

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