Stop deepfakes from defeating your voice biometrics.
Add the #1 deepfake detection to your platform with a single API call.
361+
Hours of audio analyzed
15.5%
Flagged as AI-generated
98.4%
Accuracy
80+
Languages supported
361+
Hours of audio analyzed
15.5%
Flagged as AI-generated
98.4%
Accuracy
80+
Languages supported
Trusted by voice technology leaders
The growing threat
AI changed the rules.
AI has fundamentally changed the threat landscape, and voice biometric technology needs to adapt. Voice biometrics were never designed to verify if a voice is human or not. AI cloning now generates audio that matches voiceprints — passing your authentication with no alert.
Challenges
Keeping deepfake detection up to date is time- and resource-intensive
Building in-house detection requires massive datasets, expensive compute, and a dedicated research team. We handle this so you can focus on your product.
1M+ hours
of audio required to achieve generalization across real-world situations
$100–300k
costs for a single model training run
Continuous R&D
to stay up to date on the latest voice cloning tools with recurring annual costs
Specialized talent
required to set up data processing pipelines, model architecture and training pipelines
Technology
What Makes Our Detection Different
Purpose-built for voice biometrics.
Real-Time Detection
Liveness verdicts in under 50 ms — fast enough to run inline with voice biometric matching without adding perceptible latency.
98 %+ Accuracy
Benchmark-leading detection across TTS, voice conversion, replay, and voice-cloning attacks — calibrated with confidence scores, not just binary verdicts.
80+ Languages
Language-agnostic neural architecture that generalises across accents, dialects, and telephony codecs — from 8 kHz narrowband to 48 kHz WebRTC.
Full Attack Coverage
Detects the complete spectrum of voice spoofing threats: text-to-speech, voice conversion, replay attacks, and personalised voice clones.
Continuously Updated
Model retraining against the latest synthesis engines — ElevenLabs, XTTS, RVC, Bark, and emerging open-source cloners — so detection stays ahead of attackers.
Explainable Verdicts
Every detection comes with calibrated confidence scores and segment-level localisation — not a black-box binary answer.
Integrations
Products for B2B partners
Integrate deepfake detection into your platform in minutes — via API or native SDK.
API
REST API for seamless integration with any platform or language
- Single endpoint for deepfake detection
- < 5 minutes to integrate
- On-premise Docker and Kubernetes options
- Full data-privacy, GDPR, SOC 2, ISO 27001 compliant
SDK
Install Aurigin as a package directly into your preferred code stack
- Native libraries for Python, TypeScript, and Swift
- One-line install via pip, npm, or CocoaPods
- Full data-privacy, GDPR, SOC 2, ISO 27001 compliant
Feedback
Leading technology on the market
“Having tested your tool and comparing it with the AI audio detection tools we regularly use, we are confident we can use it in our verification process.”
Deepfakes Analysis Unit
Misinformation Combat Alliance
“You've achieved 96+% accuracy overall. So, quite good.”
Evaluation
ingenID
“You have half the error rate than the next-best player we have evaluated you against.”
Competitive evaluation
Phonexia
“Having tested your tool and comparing it with the AI audio detection tools we regularly use, we are confident we can use it in our verification process.”
Deepfakes Analysis Unit
Misinformation Combat Alliance
“You've achieved 96+% accuracy overall. So, quite good.”
Evaluation
ingenID
“You have half the error rate than the next-best player we have evaluated you against.”
Competitive evaluation
Phonexia
“I ran the first files thru the web-based analyzer. The clone detection was impressive.”
Product evaluation
Tellos Alliance
“Aurigin's granular detection — identifying which segments of a recording are real vs. fake — is the first tool I've seen with this capability. It directly addresses the biggest challenge in forensic audio authentication.”
Audio/Video Forensics MSc
LJMU
“Testing showed Aurigin had best accuracy vs competitors”
Independent testing
AntiAI
“I ran the first files thru the web-based analyzer. The clone detection was impressive.”
Product evaluation
Tellos Alliance
“Aurigin's granular detection — identifying which segments of a recording are real vs. fake — is the first tool I've seen with this capability. It directly addresses the biggest challenge in forensic audio authentication.”
Audio/Video Forensics MSc
LJMU
“Testing showed Aurigin had best accuracy vs competitors”
Independent testing
AntiAI
News & recognition
Resources & Media Coverage
Our latest achievements, industry recognition, and expert insights.
#1 in Security at TOP 100 Swiss Startups 2025 Public Voting
Discover the 100 most promising Swiss startups 2025, which were selected by the Top100 Jury.
Learn more
We’re Joining Kickstart Innovation’s 2025 Cohort!
Kickstart Innovation, one of Europe’s leading open innovation platforms, announces the Open Innovation Program 2025 Startup Cohort.
Read more
“My voice is my password”: How deepfakes are triggering a voice authentication fraud crisis
Exploring the growing threat of deepfake technology to voice-based authentication systems and security measures.
Read moreFAQ
Frequently Asked Questions
Quick answers to common questions about our technology
What is Aurigin.ai?
Aurigin.ai is a deep-tech security company specializing in anti-spoofing and liveness detection for voice biometric systems.
We provide voice biometric companies, contact center platforms, and authentication providers with an API that detects synthetic, cloned, and AI-generated voices in real time — protecting biometric pipelines from spoofing attacks across 40+ languages.
How do I integrate Aurigin into my voice biometric platform?
Integration takes minutes, not months. We offer three paths:
REST API: A single HTTP call to our endpoint returns a liveness verdict in under 50ms.
Native SDKs: Drop-in libraries for Python, Node.js, and Java designed to slot into existing biometric pipelines.
On-Premise: Deploy within your own infrastructure via Docker or Kubernetes — no audio ever leaves your environment.
What is your anti-spoofing accuracy?
Our latest Apollo model achieves 98%+ accuracy on benchmark datasets covering TTS, voice conversion, and replay attacks across 80+ languages.
We consistently outperform open-source baselines and provide calibrated confidence scores — not just binary verdicts.
What types of voice spoofing attacks do you detect?
Aurigin detects the full spectrum of voice spoofing threats relevant to biometric authentication:
Text-to-Speech (TTS): Synthetic voices generated by modern neural TTS systems.
Voice Conversion (VC): AI-converted audio that mimics a specific target speaker.
Replay attacks: Previously recorded genuine audio replayed to fool biometric systems.
Voice cloning: Personalized voice models trained on small amounts of target speaker audio.
Does Aurigin store or use our audio data?
No. We take data privacy seriously and offer full control over audio handling.
Cloud API: Audio is processed securely and deleted immediately after analysis — never stored or used for training.
On-Premise: No audio ever leaves your infrastructure. Full data sovereignty.
Add Anti-Spoofing to Your Voice Platform
Join the voice biometric companies integrating industry-leading liveness detection with Aurigin.