What is AIorNot?
ai detector detects AI-generated content across text, image, audio, music and video through a REST API.
The service supports common file formats and limits (images. JPG/JPEG/PNG/WEBP/HEIC/HEIF/TIFF; audio/video. MP3/MP4; max image size 10 MB) and includes SDKs and code samples for Python, JavaScript, PHP, Go, Java and Ruby.
Detection uses pixel-level image analysis, frame-by-frame multi-model video checks, face-swap and lip-sync detection, and audio/music generator identification for source attribution.
Text analysis flags editing, paraphrasing and likely LLM-generated passages to support academic integrity, editorial review and content moderation.
Use cases include KYC and selfie verification, insurance claim validation, fact-checking and political or celebrity deepfake screening, plus music copyright and streaming protection.
API endpoints (for example /v2/image/sync) return structured detection scores and metadata for integration into automation and moderation pipelines.
Reported detection accuracy is 98.9% with fast response times (95th percentile ~1 second), enabling real-time and large-scale content verification workflows.
AIorNot pricing Free trial
Verify on the official pricing page.
Start free trialAIorNot user reviews
Would you recommend AIorNot?
AIorNot's key features
-
Multi-modal AI content detection (text, image, audio, music, video) via REST API
-
Supported file formats and limits (images: JPG/JPEG/PNG/WEBP/HEIC/HEIF/TIFF; audio/video: MP3/MP4; max image size 10 MB) with SDKs and code samples for Python, JavaScript, PHP, Go, Java, Ruby
-
Image and video detection using pixel-level image analysis and frame-by-frame multi-model checks, including face-swap and lip-sync detection
-
Audio/music generator identification for source attribution
-
API endpoints returning structured detection scores and metadata (e.g., /v2/image/sync) for integration into automation and moderation pipelines
AIorNot use cases
-
Verify incoming news tips and user-submitted media for newsrooms by running pixel-level image analysis, frame-by-frame video checks, face-swap and lip-sync detection plus text/audio attribution to provide structured scores for editorial fact-checking workflows
-
Automatically moderate and block manipulated content on social platforms and marketplaces in real time, using multimodal AI detection (image, video, audio, and text) to flag deepfakes, prioritize takedowns, and feed metadata into automated trust-and-safety pipelines
-
Secure remote identity and fraud prevention for banks and enterprises by screening video interviews, voice authorizations, and uploaded documents with face-swap detection, lip-sync checks, audio attribution, and LLM-based text provenance to stop synthetic identity and social-engineering attacks
Who is it for?
-
Developers
-
Legal teams
-
Fraud investigators
-
Claims adjusters
-
Fact-checkers
