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Our detection models are trained on adversarial datasets built from real fraud attempts, not lab conditions. That means fewer missed attacks on novel deepfakes, and results your compliance team can defend in a regulatory review.
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DuckDuckGoose combines multimodal, explainable AI with generalizable detection models to identify deepfakes across video, audio, and images. Built for sub-second speed, scalable accuracy, and GDPR-first compliance.

Stop camera-injection and deepfake videos before they can bypass liveness verification. Our real-time AI ensures fraud is caught instantly without adding user friction.
Detect deepfake impersonators during video calls. We help enterprises protect internal meetings and sensitive external collaborations from the rising threat of deepfakes and Generative AI.
Flag AI-generated or manipulated content in live broadcasts. Platforms use DuckDuckGoose to maintain viewer trust and brand safety during high stake events and townhalls.

Catch voice-cloned fraud attempts during transaction authorizations.
Our models ensure every approved payment is backed by a verified human voice.
Identify AI-driven impersonations in calls targeting decision-makers.
We safeguard sensitive communications from synthetic voice attacks designed to deceive or extort.
Detect synthetic voices during account recovery and customer support interactions. This stops fraudsters from exploiting automated or human-assisted call flows.

Detect synthetic photos and forged documents in real time. Our image analysis stops fraudulent signups before they can access your systems.
Verify visual evidence in insurance, legal, and compliance cases.
We detect tampered or AI-generated imagery to ensure decisions are based on real data.
Flag manipulated or AI-generated visuals on social and enterprise platforms. This keeps communities safe and protects brands from reputational risk.

Stop camera-injection and deepfake videos before they can bypass liveness verification. Our real-time AI ensures fraud is caught instantly without adding user friction
Detect deepfake impersonators during video calls. We help enterprises protect internal meetings and sensitive external collaborations from the rising threat of deepfakes and Generative AI.
Flag AI-generated or manipulated content in live broadcasts. Platforms use DuckDuckGoose to maintain viewer trust and brand safety during high stake events and townhalls.

Detect synthetic photos and forged documents in real time. Our image analysis stops fraudulent signups before they can access your systems.
Verify visual evidence in insurance, legal, and compliance cases.
We detect tampered or AI-generated imagery to ensure decisions are based on real data.
Flag manipulated or AI-generated visuals on social and enterprise platforms. This keeps communities safe and protects brands from reputational risk.

Catch voice-cloned fraud attempts during transaction authorizations. Our models ensure every approved payment is backed by a verified human voice.
Identify AI-driven impersonations in calls targeting decision-makers. We safeguard sensitive communications from synthetic voice attacks designed to deceive or extort.
Detect synthetic voices during account recovery and customer support interactions. This stops fraudsters from exploiting automated or human-assisted call flows.
Trained against the generators attackers are actually using. Validated on real fraud attempts, not controlled test sets", the header should contrast directly with the old positioning rather than just describe quality.
Drop-in API and SDK. Works alongside your existing KYC provider, document verification vendor, or liveness solution. Cloud, on-prem, or hybrid. Sub-second response times.
(Industry Leading Detection Accuracy)
From video to audio, our technology provides comprehensive protection across all digital formats. Whether it's safeguarding your brand, preventing identity fraud, or securing communications, DuckDuckGoose offers full-spectrum defense you can count on.

The synthetic media landscape changes every quarter. New generators, new attack types, new evasion techniques. Our models update continuously against what attackers are actually releasing, so detection does not fall behind the threat.
Industry projections put deepfake-related losses at $40 billion by 2027. The organisations absorbing those losses are using detection tools that were not built for the current generation of synthetic media. DuckDuckGoose is.
$40 billion in deepfake losses by 2027—and it’s only getting worse.

From detailed documentation for developers to easy-to-use interfaces for non-technical teams, we’ve ensured that anyone can leverage the power of AI deepfake detection.
Deepfakes themselves are not inherently illegal, but their use can be. The legality depends on the context in which a deepfake is created and used. For instance, using deepfakes for defamation, fraud, harassment, or identity theft can result in criminal charges. Laws are evolving globally to address the ethical and legal challenges posed by deepfakes.
Deepfake AI technology is typically used to create realistic digital representations of people. However, at DuckDuckGoose, we focus on detecting these deepfakes to protect individuals and organizations from fraudulent activities. Our DeepDetector service is designed to analyze images and videos to identify whether they have been manipulated using AI.
The crimes associated with deepfakes can vary depending on their use. Potential crimes include identity theft, harassment, defamation, fraud, and non-consensual pornography. Creating or distributing deepfakes that harm individuals' reputations or privacy can lead to legal consequences.
Yes, there are some free tools available online, but their accuracy may vary. At DuckDuckGoose, we offer advanced deepfake detection services through our DeepDetector API, providing reliable and accurate results. While our primary offering is a paid service, we also provide limited free trials so users can assess the technology.
The legality of deepfakes in the EU depends on their use. While deepfakes are not illegal per se, using them in a manner that violates privacy, defames someone, or leads to financial or reputational harm can result in legal action. The EU has stringent data protection laws that may apply to the misuse of deepfakes.
Yes, deepfakes can be detected, although the sophistication of detection tools varies. DuckDuckGoose’s DeepDetector leverages advanced algorithms to accurately identify deepfake content, helping to protect individuals and organizations from fraud and deception.
Yes, if a deepfake of you has caused harm, you may have grounds to sue for defamation, invasion of privacy, or emotional distress, among other claims. The ability to sue and the likelihood of success will depend on the laws in your jurisdiction and the specific circumstances.
Using deepfake apps comes with risks, particularly regarding privacy and consent. Some apps may collect and misuse personal data, while others may allow users to create harmful or illegal content. It is important to use such technology responsibly and to be aware of the legal and ethical implications.
Whether you're evaluating deepfake detection for the first time or adding a layer to an existing stack, we can walk you through deployment options, integration timelines, and what detection looks like in your specific environment.