On August 4, 2026, Modulate and Scam.ai announced a partnership that integrates Modulate's synthetic voice detection models into the Scam.ai deepfake detection platform. The combined offering lets organizations analyze images, video, and audio for manipulation through a single interface - a move that responds to a sharp rise in multi-channel scams that cost U.S. adults an estimated $68 billion in 2025.
Scam.ai already detects deepfakes in images, videos, and digital documents. By adding Modulate's voice models, customers can now examine all three primary forms of synthetic media without switching tools. A fraudulent interaction might start with a cloned phone call, move to a fabricated image, and end with a manipulated video. Defenses that only check one format can miss the broader attack.
"Scammers stopped limiting themselves to one channel a long time ago, but many detection systems are still organized around individual media formats," said Dr. Ben (Simiao) Ren, co-founder and CEO of Scam.ai. "By integrating Modulate's industry-leading models into Scam.ai, we are giving our customers a practical way to add synthetic voice detection to the platform and workflows they already use to analyze visual content."
Why voice detection matters now
Research from Gallup and the Stop Scams Alliance found that phone calls, text messages, and email each appeared in 45% of scams last year, with phone calls the most frequent primary channel. Half of all scams crossed two or more communication methods. That pattern makes standalone tools for a single medium insufficient, especially as scammers use cloned voices to establish urgency before deploying visual forgeries.
"Voice is increasingly part of coordinated multi-media deepfake scams," said Carter Huffman, CTO and co-founder of Modulate. "A convincing cloned voice can establish urgency and trust, while a fabricated video, image or document reinforces the deception." Modulate's voice detection technology reports 98.9% accuracy and a 1.1% equal error rate, holding first place on the Hugging Face Speech Deepfake Detection Leaderboard as of the announcement date. Scam.ai's Eva-v1 models report 98.2% accuracy on visual detection against internal benchmarks.
What the integrated platform does
The combined system returns confidence scores and manipulation signals for live or prerecorded audio alongside image and video analysis. Customers can add voice detection into existing fraud prevention, identity verification, and content moderation workflows without deploying separate tools. Potential use cases include digital onboarding, payment authorization, executive impersonation detection, contact center security, and insurance claims review.
The ability to evaluate an entire interaction from a single platform reduces reliance on disconnected, medium-specific tools. Scam.ai plans to make the integrated voice detection available in early September 2026.
Why this matters for PR and communications professionals
For PR and communications teams, deepfakes are a reputation and crisis-management threat. A cloned executive voice combined with a fabricated video can damage brand trust in hours. The Modulate-Scam.ai partnership offers a way to verify media authenticity before responding to incidents - and to present that verification to journalists, regulators, or the public. As part of broader AI for PR & Communications capabilities, this kind of unified detection can help teams triage threats faster. For media relations specialists specifically, AI for Media Relations Specialists learning paths address how to integrate synthetic-media detection into daily workflow and crisis planning.
Organizations interested in the integrated voice detection can request a demonstration at scam.ai.
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