Bringing accountability to image verification
VERDAT was founded on a simple premise: as AI-generated and manipulated images become indistinguishable from authentic ones, organizations need reliable tools to assess image authenticity—tools that are transparent about their methods and honest about their limitations.
We build forensic analysis technology for fraud prevention teams, compliance departments, and trust & safety operations. Our API provides the evidence and documentation these teams need to make informed decisions about image-based claims.
Our Principles
Transparency
Every analysis result includes the specific signals detected and methodology used. We believe decisions about image authenticity should be explainable and auditable.
Honest Assessment
We provide probabilistic confidence scores, not binary verdicts. Image analysis is inherently uncertain, and our outputs reflect that reality.
Privacy by Design
Images are processed in isolated environments and deleted after analysis unless explicitly retained. Your data is yours.
Continuous Improvement
As generative AI evolves, so do our detection capabilities. We maintain versioned models and transparent update cycles.
Our Approach
Image forensics is not a solved problem. Generative AI is advancing rapidly, and detection methods must evolve continuously. We're transparent about this reality.
VERDAT combines multiple analysis methodologies—metadata inspection, visual forensics, and AI-generation detection—to provide comprehensive assessments. Each method has strengths and limitations, and our scoring reflects the combined evidence.
We never claim perfect accuracy. Instead, we provide calibrated confidence scores that help teams make risk-based decisions appropriate to their specific context and requirements.