Comprehensive image analysis
VERDAT combines multiple detection methodologies to provide thorough image authenticity assessment. Every analysis produces explainable, audit-ready results.
Analysis Capabilities
Three complementary detection layers work together to identify manipulation and synthetic generation.
Metadata Analysis
Deep inspection of EXIF data, file headers, and encoding structures to identify tampering artifacts and inconsistencies.
- EXIF data extraction and validation
- File structure integrity checks
- Encoding pattern analysis
- Timestamp consistency verification
- Device signature matching
Visual Forensics
Pixel-level analysis to detect clone regions, splicing artifacts, and lighting inconsistencies that indicate manipulation.
- Clone detection and localization
- Splicing boundary detection
- Lighting direction analysis
- Compression artifact mapping
- Noise pattern analysis
AI Generation Detection
Specialized models trained to identify synthetic images from major generative AI architectures.
- Diffusion model fingerprinting
- GAN artifact detection
- Cross-generator coverage
- Version-aware detection
- Emerging model adaptation
Output & Integration
Results designed for both automated workflows and human review processes.
Probabilistic Scoring
Calibrated confidence scores that support risk-based decision thresholds rather than binary verdicts.
Structured Reports
Machine-readable JSON responses with human-friendly audit reports for compliance documentation.
Signal Explainability
Every finding includes specific evidence—locations, patterns, and technical details—for review.
Model Versioning
Each analysis records the exact detection model version used for reproducibility and audit trails.
Async Processing
Batch endpoints for high-volume workloads with webhook notifications on completion.
Data Isolation
Images processed in isolated environments with no retention unless explicitly requested.