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Spectral Analysis
A proprietary Dynamic Entropy approach is described in the source briefing as targeting phase anomalies, frequency-splicing artifacts and micro-pause patterns characteristic of synthetic audio.
Pre-kernel voice security
Protect the voice.
Before it connects.
AI Voice Guard is an infrastructure-level AI security layer designed to detect synthetic and manipulated audio in real time — before a call reaches its target device.
EDGE NPU / ON-DEVICEZero-cloud security architecture
The threat
Generative AI has weaponized the human voice.
Voice cloning and real-time synthesis can impersonate executives, financial institutions, colleagues and family members convincingly enough to defeat human judgment and traditional controls.
+442%Reported surge in vishing-related complaints in the cited market context
$450K–$600KReported average loss per deepfake-enabled incident in the cited context
$40BProjected global AI-enabled fraud losses cited for 2027
Real-timeAttackers can synthesize and manipulate voice during live interactions
Paradigm shift
Move defense below the operating system.
Instead of waiting for an application to react, AI Voice Guard intercepts inbound voice traffic at the infrastructure edge, before the target device rings.
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Network-edge interception
Calls enter through SIP infrastructure and are classified before iOS or Android becomes part of the security path.
02
Zero-Trust voice firewall
Inbound audio is isolated, analyzed and only verified low-risk calls are delivered to the end user.
03
Anti-brick architecture
The security layer is designed as infrastructure rather than an application feature, reducing dependence on device OS restrictions.
Hybrid edge AI
Spectral + semantic threat classification.
Two complementary analysis paths work together to identify synthetic-audio artifacts and manipulation intent.
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Semantic Analysis
Speech-to-text feeds a deterministic intent-recognition layer tuned to manipulation signals such as urgency and authority.
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Isolation by Discordance
Combined spectral and semantic signals create a hybrid risk decision. Below-threshold scores route calls to isolation rather than simply allowing delivery.
Beyond blocking
Turn attacks into intelligence.
The roadmap describes an Autonomous Digital Decoy that can engage suspicious callers instead of simply dropping the session.
01
Detection
A low security score can activate a decoy flow.
02
Exhaustion
An autonomous agent consumes attacker time and compute resources.
03
Profiling
The roadmap includes acoustic-fingerprint and tactic extraction for future detection.
Data sovereignty by design
Built for environments where voice data cannot leave.
The architecture is positioned for on-device processing and self-hosted enterprise clusters, including air-gapped environments.
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On-device
Designed around next-generation edge NPU execution.
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Self-hosted
Enterprise deployments can keep processing within their controlled environment.
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Zero-cloud objective
No raw voice data is intended to leave the protected environment.
“The human voice must remain the ultimate symbol of trust.”AI Voice Guard — infrastructure-level voice protection
Enterprise / regulated environments
Build the next layer of voice trust.
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