Netarx: Scaling AI-Powered Deepfake Defence

Dave Chatterjee

Product #:W50495

Supplier:Ivey

Discipline:Entrepreneurship, Information Systems

Setting:United States, 2025

Details:Case (PDF) • 7 pages • 2026-07-16

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In late 2025, Sandy Kronenberg, founder and chief executive officer of Netarx, reviewed an increasingly familiar incident report. Acting on what appeared to be an urgent executive request delivered through a convincing combination of synthetic video, cloned voice, and spoofed email, an enterprise employee had authorized a high-value transaction. The loss approached $500,000.

Netarx had built its platform for precisely this emerging threat of deepfake-enabled fraud, driven by artificial intelligence (AI) to detect synthetic impersonation across video, voice, and email in real time. Its “Flurp” (real-time trust indicator) system translated complex model outputs into intuitive signals for end users. With these frauds accelerating rapidly toward enterprise-scale risk, Netarx had proven its technical approach and enterprises expressed interest in “AI versus AI” protection. However, the path to scalable growth hinged on more complex leadership challenges such as privacy, accuracy, deployment, and user adoption. Could Netarx scale its platform and go-to-market approach quickly enough to keep pace with an exponentially evolving threat landscape, without overwhelming customers operationally or eroding trust? How could innovators scale trust as quickly as technology when the threat itself targeted human perception?

Learning Objectives

This case is appropriate for graduate courses in master of business administration (MBA), executive MBA, master of cybersecurity, or technology management programs, as well as executive education modules on AI governance and adoption, cybersecurity strategy and leadership, digital trust, and innovation scaling.

After completing this case, students will be able to do the following:

Understand the trust gap, examine why organizations remain vulnerable to deepfake-enabled fraud despite heavy investment in traditional cyber defences, and explore Netarx’s value proposition as a business response to a human-centric threat.
Evaluate multimodal AI detection and analyze the risks, benefits, and governance imperatives of deploying ensemble AI inference systems to protect human decision-making in real time.
Apply the Commitment–Preparedness–Discipline (CPD) framework to assess how organizations can responsibly integrate deepfake defence into enterprise security operations.
Debate trust and adoption challenges and explore how an emerging firm can persuade cross-functional, risk-averse enterprise buyers to adopt a novel and categorically new class of security technology.
Assess strategic scaling choices and evaluate the trade-offs between broad enterprise-wide deployment and targeted high-risk deployments and how that positioning shapes adoption speed and customer confidence.