The Communication Integrity Layer

SYNHAWK’s technology builds on over three years of applied research originating from Stanford University, UC Berkeley, and Google DeepMind, with our research team based in San Francisco and engineering in Prague.

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.

Today’s SYNHAWK platform detects synthetic media with purpose-built foundation models. But we are already building the next layer: cryptographic provenance — key-based verification that authenticates communication at the source.

As generative AI narrows the gap between real and synthetic signals, detection alone will not be enough.

Provenance makes trust tamper-proof — verifiable by design, not by inference.

SYNHAWK is building toward a future where every voice and video signal carries proof of its origin.