Detect Voice Deepfakes in 2.1 seconds.

Modulate's AI Model, Velma, can identify synthetic voice fraud in real time, protecting your calls, customers, and revenue - at 120x lower cost than the next leading provider.

#1 Ranked for Deepfake Detection on Hugging Face’s Leaderboard
Save 99% over the competition
Direct API access & developer docs available
ISO 27001 Certified
100M+ Users Protected

See Velma Detect a Deepfake Live

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Modulate Catches 99% of all Deepfakes

Catch 2x more deepfakes and flag 48% fewer false positives vs. next-best. 🤗 Hugging Face Leaderboard.
Accuracy
92
94
96
98
100%
98.9%
Modulate
velma-deepfake-detect
97.9%
Hiya
authenticity-verific
97.4%
Resemble AI
resemble-detect-3b
96.9%
Whispeak
whispeak
96.0%
Deep Learning
dlmsl-speaksure-v0.1
94.2%
DF Arena
df-arena-500m-v1
94.1%
DF Arena
df-arena-1b-v1
93.9%
Syntra
syntra-detector
92.9%
Momenta
momenta

#1 AI Model for Deepfake Detection

Velma outperforms every published deepfake detection model including Resemble AI, Hylia, and Whispeak.

  • ✓  Catch 133% more deepfakes and flag 48% fewer false positives
  • ✓  Starts at $0.25 / hour, compared to $29 / hr with the next leading provider
  • ✓  Voice-native, multi-modal AI designed to handle real-world audio
  • ✓  100M+ users protected annually across enterprise organizations

Detect Deepfakes for just $0.25 / hr

Fraud protection at scale, at a price that levels the playing field vs. scammers.
Modulate Deepfake-Detect
$0.25 / hr
Resemble AI Enterprise
$29 / hr
Other Providers
$30 — $120 / hr
Resemble AI Self-Serve
$144 / hr

Voice Fraud Is the Fastest-Growing Attack Vector


AI voice cloning tools are cheap, fast, and widely available. Attackers need just 3 seconds of audio to
generate a convincing synthetic voice.

900%

Annual Growth Rate
Deepfakes surged from 500K in 2023 to 8M in 2025

$40B

By 2027
Projected deepfake fraud losses

3s

To Clone a Voice
85% accuracy with just 3 seconds of audio

$600K+

Average Loss
Per deepfake attack incident

Four Detection Layers Work Together

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Audio Forensics

Identify subtle waveform and audio quality artifacts from synthetic voice generation.

Audio Forensics icon

Emotion Modeling

Detect shallow or muted emotional expression typical of synthetic voice deepfakes.

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Linguistic Profiling

Uncover signs of scripted or AI-generated dialogue — unusual diction, pacing, or verbosity.

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Conversational Dynamics

Analyze flow patterns, turn-taking, and timing to flag robotic or unnatural exchanges.

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Protecting Every Sector That Relies on Voice

Banking & Finance

AI vishing attacks impersonating bank reps, wire transfer fraud, and IVR authentication bypass.

Healthcare

Patient impersonation, prescription authorization fraud, and insurance verification attacks.

Retail & E-Commerce

Refund and return fraud, gift card scams, and account takeover via voice channels.

Insurance

Synthetic voice claims fraud, fraudulent policy changes, and impersonation of policyholders.

Higher Education

Financial aid fraud, student record impersonation, and registrar call fraud.

Enterprise Contact Centers

AI-assisted social engineering, executive impersonation (vishing), and high-volume inbound fraud.

Built for Developers.
Trusted by Enterprises.

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Simple API integration

REST and streaming APIs designed to plug into existing infrastructure with minimal lift.

Real-time decisioning

Analyze audio in seconds and return actionable signals fast enough for live interactions.

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Low latency, high throughput

Get results from as little as ~2.5 seconds of audio, optimized for production environments.

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Flexible deployment

Use in batch pipelines or real-time systems like contact centers, authentication flows, or moderation pipelines.

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Frequently Asked Questions

Does Velma work on recorded and live calls?

Yes. Velma supports both real-time streaming and batch analysis of recorded audio files, giving you full coverage across your call library.

What is AI voice deepfake fraud — and how is it different from vishing?

Vishing is social engineering over the phone — tricking someone into revealing information or authorizing a transfer. AI voice deepfakes add a synthetic voice layer on top: attackers clone a trusted person’s voice to make the scam convincing. Velma detects both the synthetic voice signature and the behavioral fraud patterns that accompany it.

Can Velma distinguish legitimate synthetic voice users (e.g., assistive technology)?

Yes. Velma’s conversational analysis layer looks beyond voice type to intent, urgency cues, scripted phrasing, and turn-taking anomalies — distinguishing fraudulent callers from users who rely on assistive voice technology. This prevents false positives that would harm accessibility-dependent customers.

Does Velma detect video deepfakes?

Velma analyzes audio only — by design. The overwhelming majority of voice fraud happens over phone and contact center channels, not video. Purpose-built audio analysis delivers higher accuracy and lower cost at scale than generalist multimodal tools that try to do everything.

How much does Velma Deepfake Detect cost?

Velma offers usage-based pricing at a 120x improved rate compared to the competition, starting at $0.25/hour. For more information, see our Pricing page.

Ready to Stop Voice Deepfakes?

Book a live demo and see Velma detect a synthetic voice attack in real time. No commitment required.

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