WILMINGTON, Del., June 04, 2025 (GLOBE NEWSWIRE) -- Mental health is an urgent concern for students across South Africa, especially in underserved communities with limited access to care.

To help close this gap, the University of KwaZulu-Natal (UKZN) , Valio Technologies , and Brand Engagement Network Inc. (BEN) (NASDAQ: BNAI) are launching an inclusive, AI-powered mental health program that offers private, 24/7 support.

The initiative starts with UKZN students and will help shape how mental health support is expanded across the region.

“AI is now playing a vital role in improving access to mental health support,” said Paul Chang, CEO of Brand Engagement Network. “This collaboration shows how our iSKYE platform delivers meaningful help in areas where traditional care is out of reach.”

BEN’s AI-powered platform offers personalized mental health support, 24 hours a day, 7 days a week.
It enables ongoing check-ins, emotional support, and curated mental health resources, especially for individuals without access to traditional therapy.

The solution is designed to scale across diverse populations, particularly in remote or under-resourced communities.

Unlike scripted bots, BEN’s AI adapts to each individual, offering emotionally aware conversations, personalized guidance, and anonymized insights that help institutions better target support while maintaining full privacy protections.

“We are honoured to work with the University of KwaZulu-Natal on this mission-driven initiative,” said Lefentse Nokaneng, CEO and Founder of Valio Technologies. “Together, we’re redefining how institutions support mental wellness at scale—using AI to build trust and access.”

The co-development effort is already underway, with a launch at UKZN planned for later this year.

Insights from this rollout will help shape future expansions, ensuring the program stays responsive to students and communities across the region.

About Brand Engagement Network (BEN)
Brand Engagement Network Inc. (NASDAQ: BNAI) innovates in AI-powered customer engagement, delivering safe, intelligent, and scalable solutions. Its proprietary Engagement Language Model (ELM™) and Retrieval-Augmented Generation (RAG) architecture enable highly personalized interactions supported by customers’ curated data in closed-loop environments. BEN develops AI-driven engagement solutions for the life sciences, automotive, and retail industries, featuring AI-powered avatars for outbound campaigns, inbound customer service, and real-time recommendations. With a global AI research and development team, BEN provides secure cloud-based or on-premises deployments, granting complete control of the technology stack and ensuring compliance with GDPR, CCPA, HIPAA, and SOC 2 Type 1 standards. The company holds 21 patents, with 28 pending, demonstrating its commitment to advancing AI-driven consumer engagement. For more information, visit www.beninc.ai .

About Valio Technologies
Valio (Technologies Pty Ltd) is a Pan-African technology company specializing in the development of disruptive enterprise blockchain, Robotic Process Automation (RPA), and Artificial Intelligence solutions tailored for developing markets. With a strategic focus on key sectors such as healthcare, automotive, mining, and supply chain management, our mission is to lead Africa into the Fourth Industrial Revolution. Valio is dedicated to transforming these sectors by harnessing innovation to foster sustainable development and economic growth across the continent. For more information, visit www.valiotechnologies.com .

About the University of KwaZulu-Natal (UKZN)
The University of KwaZulu-Natal is a leading research and teaching institution in South Africa, committed to academic excellence and community engagement. With campuses across the province of KwaZulu-Natal, UKZN focuses on advancing inclusive development and sustainable well-being through innovation, education, and partnership. For more information, visit www.ukzn.ac.za .

Forward-Looking Statements
Certain statements in this communication are "forward-looking statements" within the meaning of federal securities laws. They are made pursuant to the safe harbor provisions of the Private Securities Litigation Reform Act of 1995. These forward-looking statements reflect, among other things, BEN’s current expectations, assumptions, plans, strategies, and anticipated results. Because forward-looking statements relate to the future, they are subject to inherent uncertainties, risks, and changes in circumstances that may differ materially from those contemplated by the forward-looking statements, which are neither statements of historical fact nor guarantees or assurances of future performance.

There are a number of risks, uncertainties and conditions that may cause BEN’s actual results to differ materially from those expressed or implied by these forward-looking statements, including but not limited to the risk factors described in Part I, Item 1A of Risk Factors in BEN’s Annual Report on Form 10-K for the year ended December 31, 2023 and the other risk factors identified from time to time in the BEN’s other filings with the Securities and Exchange Commission (the "SEC"). Filings with the SEC are available on the SEC's website at http://www.sec.gov .

Many of these circumstances are beyond BEN’s ability to control or predict. These forward-looking statements necessarily involve assumptions on BEN’s part. These forward-looking statements may include words such as "believe," "expect," "anticipate," "estimate," "intend," "plan," "project," "should," "may," "will," "might," "could," "would," or similar expressions. All forward-looking statements attributable to the Company or persons acting on BEN’s behalf are expressly qualified in their entirety by the cautionary statements that appear throughout this communication. Furthermore, undue reliance should not be placed on forward-looking statements, which are based on the information currently available to the Company and speak only as of the date they are made. BEN disclaims any intention or obligation to update or revise publicly any forward-looking statements.

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