Innovative real-time text-to-action AI engine that filters scam calls as a critical infrastructure investment, protecting customers, reducing enterprise fraud losses, ensuring regulatory compliance, and creating new revenue opportunities for telecom operators and financial institutions.
Lost annually to phone scams in the U.S. (2024), with financial institutions bearing $4.41 for every $1 of fraud.
Americans were victims of phone scams in the past 12 months.
Higher than any other fraud type. Voice channel fraud losses spiking across industry.
SIP or SS7 integration mirrors live audio inside the operator core without affecting call quality.
Speech is converted to text and evaluated by an LLM within 1–2 seconds.
The system can warn users, tag sessions, or terminate high-risk calls based on operator policy.
Traditional solutions rely on call metadata—numbers, frequency, or historical patterns. CallSentinel analyzes the actual conversation, identifying intent, manipulation tactics, and behavioral signals in real time. This enables detection of scams that would otherwise bypass metadata-based systems.
Most fraud systems act after the damage is done. CallSentinel operates during the call, detecting threats as they unfold and enabling immediate intervention—before money is lost or sensitive information is exposed.
Instead of relying on end-user apps or opt-in solutions, CallSentinel is deployed at the telecom infrastructure level. This provides automatic protection for all users, without requiring installation, behavior change, or user awareness.
Generic AI models are not built for real-time, high-stakes environments. CallSentinel's AI is optimized for low-latency decision-making and consistent outputs, ensuring fast, reliable, and predictable performance suitable for telecom-grade systems and regulatory requirements.