Companies are facing a surge in AI impersonation scams, prompting imper.ai to launch a new detection technology aimed at preventing these attacks in real time. The startup recently secured $28 million in funding to develop its system that combines organizational context with risk scoring, specifically targeting social engineering threats. Traditional impersonation methods are evolving, and attackers are increasingly using AI tools to mimic voices, faces, and even create fake profiles. Imper.ai's approach focuses on more than just identifying impersonation. It analyzes device fingerprints, network conditions, and digital identity signals to spot potential threats before they escalate. For instance, it can detect fake requests from someone posing as a CEO, halting fraudulent wire transfers or unauthorized credential resets. The technology is designed to flag suspicious communications across multiple channels, including email, voice calls, video meetings, and messaging platforms like Microsoft Teams. The detection process is designed for efficiency. Imper.ai claims its system works without requiring installations or additional agents, allowing for seamless integration into existing workflows. By providing real-time risk assessment, organizations can maintain security without compromising on privacy or collaboration speed. The aim is to stop social engineering attempts before they even start, reinforcing defenses across all communication channels.