Detect Deepfakes Instantly with Raid AI
Real-time deepfake detection across audio, image, and video for enterprises.
Raid AI protects meetings, calls, and communications with multimodal
AI-powered detection: 98% accuracy and sub-50ms latency for audio across
100+ languages, plus visual analysis for face swaps, synthetic images,
and manipulated video.
Why organizations choose Raid AI
- 98% detection accuracy for audio deepfakes across phone, video conference, and recorded media.
- Sub-50ms latency for real-time protection during live calls and meetings.
- 100+ languages supported with specialized Arabic dialect coverage.
- Image detection for face swaps, AI-generated faces, and manipulated photographs.
- Video detection for face-swap videos, lip-sync manipulation, and fully AI-generated content.
- Zero data retention — all media analyzed in memory and immediately discarded.
- Cloud API and on-premise air-gapped deployment options available.
Privacy-by-design analysis
Raid AI analyzes audio, image, and video files entirely in memory and discards
them immediately after processing. No media is logged, stored, or used to retrain
models. This zero-retention architecture is intentional — it lets regulated
industries adopt deepfake detection without expanding their data-handling surface
or triggering new privacy reviews.
Cross-modal detection in one platform
Most detection vendors specialize in a single modality. Raid AI covers audio,
image, and video in one platform, which matters because real attacks combine
channels — a deepfake video call with a cloned voice, or a forged ID image
attached to a vishing call. One vendor, one API, one auditable pipeline.
Built for global enterprises
Raid AI's audio detection supports more than 100 languages with specialized
accuracy for Arabic dialects, a coverage profile most academic and
English-trained models lack. Image and video analysis is language-independent.
The combination matters for multinational banks, government agencies, and media
organizations operating across regions where attackers exploit linguistic blind
spots in detection tooling.
How Raid AI Works
- Upload or stream media through our dashboard, WhatsApp, or native integrations with Microsoft Teams, Zoom, Google Meet, Slack, and Webex.
- AI-powered analysis examines frequency patterns, vocal biomarkers, visual artifacts, and facial geometry to identify synthetic content.
- Real-time verdict with confidence score in under 50 milliseconds.
- Report and act with forensic reports, compliance exports, and automated SOC alerts.
Audio detection signals
Audio analysis looks for the artifacts generative voice models struggle to
reproduce: unnatural harmonic ratios, missing breathing noise, abnormal spectral
rolloff, and inconsistencies in vocal biomarkers like pitch and cadence. The
pipeline tolerates compression and background noise, so detection works on phone
calls and mobile recordings rather than only on lab-quality input.
Image and video detection signals
Image and video analysis examines pixel-level artifacts left by GAN and diffusion
generators, facial geometry inconsistencies, lighting mismatches, and temporal
coherence across frames in video. Face-swap detection focuses on blending
boundaries and unnatural texture transitions where the source face was composited
onto the target. The models handle compressed and re-encoded media common on
social platforms.
Integration and deployment models
Raid AI offers a REST API for custom pipelines, webhooks for event-driven flows,
and native integrations with Microsoft Teams, Zoom, Google Meet, Slack, Webex,
and WhatsApp. Cloud deployment runs on Raid AI infrastructure; on-premise and
air-gapped deployments run inside the customer's network for organizations with
strict data sovereignty requirements.
Use Cases
Financial services and CEO voice fraud
Individual deepfake CEO fraud incidents have produced losses exceeding $35 million.
Raid AI deploys on the voice channels that handle treasury, wire transfer, and
financial authorization calls. Sub-50-millisecond verdicts flag synthetic speech
before the agent completes a fraudulent request, and the accompanying forensic
report supports investigation and recovery.
Call centers and video KYC
Customer verification flows in contact centers and BPO operations now face cloned
voices and synthetic ID images, both of which can defeat traditional voice
biometrics and document-OCR checks. Raid AI verifies that the voice on the call
is real and that any submitted face image or video has not been generated or
face-swapped, before accounts are unlocked or transactions authorized.
Government and regulated air-gapped deployment
Government agencies, intelligence services, and defense organizations need
detection that runs entirely inside their own infrastructure with no internet
egress. Raid AI's on-premise air-gapped deployment option ships the same audio,
image, and video models customers run in cloud, so analysts can verify diplomatic
channels, intercepted media, and field intelligence without exposing the content
to a third party.
Frequently Asked Questions
Does Raid AI store or retain your data?
No. Raid AI does not store, log, or reuse uploaded audio, images, or video
files. All analysis is performed securely in memory, and data is discarded
immediately after processing to ensure full privacy and compliance.
How is Raid AI different from other deepfake detection tools?
Unlike most competitors that focus on a single modality or are biased toward
English-only datasets, Raid AI detects deepfakes across audio, image, and video.
Audio detection covers Arabic dialects and over 100 languages with sub-50ms
latency, while image and video analysis extends the same multimodal defense to
face swaps, synthetic media, and manipulated visual content.
Can Raid AI be used in real-time scenarios like calls or meetings?
Yes. Raid AI supports real-time and near real-time detection across all media
types, analyzing live audio streams during VoIP calls and online meetings and
detecting face swaps in conference video feeds. It integrates natively with
Microsoft Teams, Zoom, Google Meet, Slack, Webex, and WhatsApp to stop deepfake
attacks as they happen.
Who is Raid AI built for?
Raid AI is designed for financial institutions, contact centers and BPO
operations, enterprise meeting platforms, government agencies, and media
verification teams. It is used anywhere voice, image, or video communication
drives business-critical decisions and the cost of a successful deepfake attack
is high.
Do I need technical or coding skills to use Raid AI?
No. Raid AI offers an easy-to-use dashboard with drag-and-drop uploads for
audio, image, and video files. For developers and integration teams, it also
provides a REST API that can be added to any media pipeline with a few lines of
code.
How accurate is Raid AI's deepfake detection?
Raid AI achieves 98% detection accuracy for audio deepfakes across diverse
conditions including phone calls, video conferences, compressed streams, and
recorded files. Image and video deepfake detection capabilities are also
available, with models continuously trained on the latest AI generation
techniques across all three modalities to keep pace as deepfake technology
evolves.
What languages does Raid AI support?
Raid AI's audio detection supports over 100 languages and dialects with
specialized accuracy for Arabic dialects, a key differentiator in the market.
Our multilingual models are trained on diverse linguistic datasets to ensure
reliable detection regardless of the speaker's language or accent. Image and
video analysis is language-independent and works globally.
How fast is Raid AI's detection?
Raid AI delivers audio detection results in under 50 milliseconds (sub-50ms
latency), enabling real-time protection during live calls and meetings. Image
and video deepfake analysis is also available, allowing security teams to verify
visual media alongside audio for comprehensive multimodal protection.
Glossary
Deepfake
Synthetic media generated by AI to impersonate a real person. A deepfake is
synthetic audio, image, or video content generated by artificial intelligence
that imitates the appearance or voice of a real person.
Deepfake Detection
Technology that identifies AI-generated synthetic media. Deepfake detection is
the process of analyzing audio, image, or video content to determine whether it
was generated or manipulated by AI rather than captured from a real source.
Deepfake Audio
AI-generated speech designed to sound like a specific human speaker. Deepfake
audio refers to speech synthesised by machine learning models that replicate a
target person's voice, tone, cadence, and accent.
Deepfake Image
AI-generated or manipulated face images used for impersonation or fraud. A
deepfake image is a photograph that has been generated or manipulated by AI to
depict a person in a fabricated scenario.
Deepfake Video
Face-swapped, lip-synced, or fully AI-generated video content. A deepfake video
is video content that has been generated or manipulated by AI to alter the
appearance, expressions, or actions of people in the footage.
Voice Cloning
AI replication of a target person's voice from sample audio. Voice cloning is
the use of machine learning to recreate a specific person's voice from a short
audio sample.
Face Swap
Replacing one person's face with another in images or video using AI. A face
swap is an AI technique that replaces one person's face with another's in an
image or video while attempting to preserve realistic lighting, skin tone, and
facial expressions.
Synthetic Media
Any media created or significantly modified by artificial intelligence.
Synthetic media is a broad term for any audio, image, video, or text content
produced or substantially altered by AI.
Audio Liveness Detection
Verification that audio comes from a live human rather than a replay or
synthesis. Audio liveness detection is the process of confirming that a voice
sample originated from a real, present human speaker, rather than a recording,
replay attack, or AI-generated synthesis.
CEO Fraud
A fraud scheme that impersonates a company executive to authorize payments. CEO
fraud, also called business email compromise (BEC) or whaling, is a scheme where
attackers impersonate a senior executive to trick employees into wiring money or
disclosing sensitive data.