DetectifAI

DetectifAI: Foundation Models for Voice Authenticity

DetectifAI builds language-agnostic foundation models designed to detect synthetic speech, verify speakers, and stop voice impersonation across calls, devices, and AI systems. The platform focuses on securing high-risk voice conversations, primarily within financial services, by ensuring that voice interactions are authentic and identities are accurately verified.

Key Features

• Deepfake Detection: Inspects speech segments at the operating threshold to detect synthetic, cloned, manipulated, or replayed speech inside live calls and audio workflows.

• Speaker Verification: Compares a live voice with an enrolled reference to verify that the speaker matches the claimed identity.

• AI Voice Agents and Assurance: Combines authenticity, identity, context, and policy to ensure automated systems act safely and decisions can be defended with preserved evidence.

• High-Speed Processing: Achieves a 24 ms per-clip latency and processes 119 hours of audio per compute-hour, ranking as the fastest commercial system on the September 2026 Podonos benchmark.

• High Accuracy: Catches 97.3% of synthetic files with a 94.47% overall accuracy rate, successfully evaluating files without any rejected samples.

• Flexible Deployment: Models can run hosted via Cloud API, inside a private VPC or on-premises security boundary, or directly on the telephony edge device where the call arrives.

• Resilience to Channel Conditions: Designed to survive lossy telephony, including codecs, packet loss, resampling, compression, noisy rooms, and cheap microphones.

Use Cases

• Financial Services Security: Securing high-risk voice conversations and transactions for financial institutions by verifying if a voice is real.

• Contact Center Authentication: Verifying caller identity and detecting fraud across PSTN, VoIP, mobile networks, and contact-center infrastructure.

Getting Started

Website: https://detectif.ai

DetectifAI provides a comprehensive voice-intelligence stack that allows organizations to inspect audio signals, preserve evidence, and route outcomes securely before trusting a voice.