AI Image Detector

What It Does

AI Image Detector is a forensic screening tool that determines whether an image was AI-generated or is a real photograph. Unlike typical detectors that return a single confidence percentage, this tool runs four independent detection models in parallel and applies a published weighted-vote rule to produce graded conclusions—from "AI-generated" to "No AI detected"—with full transparency about how each engine voted.

Who It's For & Problem Solved

Designed for anyone who needs to verify image authenticity before making decisions: dating app moderators screening profile photos, educators investigating student submissions, artist communities protecting human-made work, journalists fact-checking viral images, and e-commerce teams catching generated product shots. The core problem it solves is trust: when a picture's authenticity matters, users need evidence they can defend, not a black-box guess.

Key Features & Capabilities

• Four independent detection engines: Sightengine GenAI, Winston AI, Was It AI, and the open-source SAFE model (KDD 2025) all vote on every report, with results attributed by name
• Deterministic trump card: C2PA credentials and generator self-tags are checked first and override model votes when present
• Batch processing: Upload up to 50 images at once, receive a triage summary plus CSV export for moderation queues
• Graded conclusions: Five-tier verdicts (AI-generated, Likely AI-generated, Inconclusive, Likely real, No AI detected) with transparent disagreement reporting
• Generator coverage: Detects fingerprints from Midjourney v5–v7, DALL·E, ChatGPT, Stable Diffusion, Flux, Google Imagen, Adobe Firefly, Ideogram, and GAN-based synthetic portraits
• Forensic reporting: SHA-256 hash recording, shareable report links, downloadable PDFs for chain-of-custody documentation
• Automatic refunds: If a detection engine fails, its credit portion refunds automatically

Typical Workflows

Users upload untouched original images (JPEG, PNG, or WebP up to 12MB). The system runs all four models in parallel, checks metadata for C2PA or generator tags, and synthesizes the votes into a single graded conclusion. Reports display each engine's vote by name, flag disagreements explicitly, and provide visual inspection evidence. Batch workflows let moderation teams triage dozens of images at once, exporting results to CSV for downstream review.

What Differentiates It

Transparency and multi-signal consensus set AI Image Detector apart. Where competitors hide engine disagreement behind a single number, this tool reports conflict openly—"Inconclusive" is a valid answer. The published weighted-vote rule is auditable, the open-source SAFE model runs on the provider's own hardware for independence, and every report names which engines contributed. The first full report is free with no card required, and pricing scales by volume without feature gating.