HAWK 7
Real-Time Deepfake Voice Detection Analyzes live voice streams and detects AI-generated or cloned speech.
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VYRA 9
Real-Time Deepfake Video Detection Detects manipulated video or fake visuals in live or recorded streams.
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PRIVA 3
Deepfake Audio & Image Verification
Authenticates voice messages and photos on WhatsApp, Telegram, or Signal.
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AURA ID
Prominent Individual Protection
Screens social media and other prominent channels for any manipulated or AI-generated content with the customer’s likeness.
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We build foundation models that verify the authenticity of audio, video, and identity - from telco infrastructure to messaging apps.
Communication can no longer be taken at face value.
The integrity of human communication requires a new kind of protection.
Our Models:
Foundation Model for Audio
Understands the structure of human speech at the signal level. Identifies synthetic, cloned, or manipulated audio in real time across live calls and recorded streams.
Use Cases: Telco networks, call centres, enterprise communications, messaging platforms.
0.1
Foundation Model for Video
Analyses spatial, temporal, and compression patterns to verify the authenticity of video content. Detects generated, manipulated, or composited video in live and recorded streams.
Use Cases: Video calls, KYC verification, media platforms, remote interviews.
0.2
Consumer Protection Suite
Brings the power of HAWK 7 and VYRA 9 to everyday communication. Verifies the authenticity of voice messages, photos, and video across messaging platforms and the web.
Use Cases: Individuals, families, organizations — on WhatsApp, Telegram, Signal, and web browsers.
0.3
Identity Protection Suite
Continuously monitors social media, websites, and public channels for unauthorised use of a person’s voice or likeness. Alerts and provides actionable intelligence for takedown.
Use Cases: Executives, government officials, public figures, brands.
0.4
Each module works standalone or within the unified SYNHAWK platform.
SYNHAWK continuously analyzes voice, speech patterns, and visual cues, distinguishing genuine signals from machine-generated ones, and intercepting manipulation before it spreads through the network.
Where traditional cybersecurity protects code and access, SYNHAWK protects the communication signal itself, and does it at the scale of global networks that connect individuals, societies, and governments.
Today, SYNHAWK detects AI-enabled manipulation with purpose-built foundation models. But detection alone has a shelf life. The next phase introduces cryptographic provenance — key-based verification that authenticates communication at the source. Detection is the bridge. Provenance is the destination.
Built from Research. Deployed at Network Scale.
This scientific foundation ensures that every SYNHAWK deployment is not just a product — but an extension of state-of-the-art AI safety research.
projected US losses from generative AI fraud by 2027 (Deloitte)
of voice impersonation attacks against enterprises that succeed (GSMA)
people globally exposed to AI-generated manipulation (McAfee / GCA)
Regulatory Drivers:
NIS2 · AI Act · DORA · GDPR — all mandate media authenticity and communication integrity.
Designed for carrier-grade environments. No changes to user experience. Invisible to end users, critical for network operators.
API & SDK - REST API and embedded SDK for direct integration into your communication stack
On-Premise & Edge - Run inference within your own perimeter - air-gapped, sovereign cloud, or edge deployments
Network-Native - Full interoperability with SIP, IMS, CCaaS, and call-recording infrastructure
We believe that the ability to trust what you hear and see is foundational to every relationship, institution, and network. As AI makes it trivial to generate convincing synthetic media and manipulate, we’re building the technology to ensure that authenticity remains verifiable - anywhere communication happens. Because the next frontier isn’t code - it’s the integrity of the human signal and the connections that depend on it.
ENISA Threat max-[1023px]: landscape 2024 + MIT Tech Review AI Threat Outlook“AI-generated voice phishing expected to account for over 50% of vishing incidents by 2025.”
Deloitte
Predicts that generative AI could cause losses of up to 40 billion USD in the United States alone by 2027, with an annual growth rate (CAGR) of around 32%.
GSMA - Combating Vishing: An Analysis of Voice Call Impersonation and Emerging Defences
“77% of vishing attacks against enterprises are successful, giving attackers access to finances, data, and personal identities.
”McAfee – Global Scam Report + projekce GCA (Global Cyber Alliance)
“10% of the global population has already encountered AI-generated scams.”
ENEA – Almost Two Thirds of Enterprises Suffer Significant Losses to Mobile Fraud
“61% of enterprises reported significant losses due to mobile fraud - including vishing and deepfake attacks.”
