Platform — Securing the Human Signal Across Global Networks

SYNHAWK’s technology builds on over three years of applied research originating from Stanford University, UC Berkeley, and Google DeepMind.



Our methods and models have been presented at top-tier AI conferences — CVPR, ICLR, and IJCAI — and validated through partnerships with UNICEF, the Hoover Institution, and global security agencies.

Members of the research team have advised multiple governments — including the United Kingdom, Singapore, Switzerland, and the United States — on deepfake defence and AI threat mitigation.


SYNHAWK models are already operating in production environments at LinkedIn and YouTube, enhancing large-scale synthetic media detection.

This scientific foundation ensures that every SYNHAWK deployment is not just a product — but an extension of state-of-the-art AI safety research.

At the core of SYNHAWK lies the Trust Engine — a modular AI system that monitors voice and video streams in real time.

It identifies the subtlest acoustic and visual signatures of synthetic media, providing a live trust score for each interaction.

This enables telecom operators, enterprises, and institutions to detect and neutralize deepfake intrusions before they reach the user.

The platform is built for regulatory environments, ensuring full compliance with GDPR, NIS2, and the EU AI Act — with audit-ready transparency at every stage of inference.