Problem

GetReal addresses the breakdown of trust caused by AI-generated identities, deepfakes, and manipulated media. Conventional authentication checks a password, device, or face at a single point in time, but does not establish that the human on a call or phone is genuine; increasingly realistic face and voice cloning lets attackers impersonate employees, executives, customers, and job candidates. The economic pain is fraud, compromised access, compliance exposure, and loss of trust: GetReal cites a $25 million loss from a real-time video-conferencing attack, while its materials report that 62% of organizations experienced a deepfake attack in the prior 12 months.

The clearest near-term use case is remote hiring and onboarding, where fabricated identities and deepfake interviews can place impostors—including potentially nation-state operators—inside an enterprise. Other high-value scenarios include executive communications, financial approvals, customer interactions, and help-desk account recovery, where an attacker can exploit a trusted live interaction before ordinary credentials or controls reveal the compromise.

Product / Service

GetReal Protect is the company’s flagship enterprise product and part of its broader GetReal Trust & Authenticity Platform. It combines multimodal deepfake detection, impersonation detection, continuous identity verification, threat intelligence, attack-surface visibility, and automated response. The platform analyzes audio, video, images, files, and live digital interactions, correlating content, biometric, behavioral, and contextual signals to determine whether a person and interaction are authentic.

The product is designed for workflow-ready deployment across enterprise security and collaboration environments, including Microsoft Teams and Cisco Webex, with Zoom coverage announced as forthcoming. Rather than relying only on a one-time login check, GetReal continuously verifies identity during high-risk interactions and provides forensic-grade, explainable signals so security teams can detect, investigate, and respond to synthetic-media attacks in real time. Its stated benefit is to prevent fraud and restore trust without collecting or sharing participant data without consent.

Market

GetReal competes in the emerging enterprise deepfake-detection, synthetic-media security, digital forensics, and identity-defense market. Its positioning is broader than a file scanner: it combines media authenticity analysis with continuous identity assurance and policy enforcement inside real-world workflows. Named alternatives and adjacent competitors include Reality Defender, identifAI, Netarx, Originality.ai, Deep Media, Facia, AU10TIX, Sensity AI, Hive, and Pindrop, although the precise competitive set varies by whether the buyer prioritizes deepfake detection, identity verification, fraud prevention, or voice security.

The company appears to be venture-backed and commercially active rather than an unlaunched research project: it announced a $17.5 million Series A, has expanded live protection to major collaboration platforms, and was named a Market Shaper in Gartner’s 2026 Emerging Market Quadrant for Deepfake Detection—Startup Vendors. Public materials reviewed here do not disclose revenue, customer counts, or profitability, so GetReal’s exact commercial scale and whether it is revenue-generating cannot be determined from the available evidence; the disclosed funding, product availability, platform expansion, and Gartner recognition are the clearest public traction signals.