Real-Time AI
Trust Index™
Defending Truth. Securing Infrastructure. Aligning Models.
We benchmark, audit, and mathematically secure our neural networks in real time across 2,660 images spanning 5 independent datasets. Inspect live reliability weights, explainability indices, and safety consensus matrices.
Controlled Model Alignment
Our unified consensus index aggregates cross-generator generalization, real-world resiliency, and 3-model weighted ensemble accuracy.
Consensus Audit Scanner
Initiates a distributed audit signature check across 2,660 benchmark images. Zero risk to telemetry stability.
Official ZSure Benchmark Scores
Measured across 2,660 images spanning 5 independent public and internal benchmark datasets.
| Dataset | N | Accuracy | AUC-ROC | What It Tests |
|---|---|---|---|---|
| Cross-Generator Benchmark | 2000 | 96.3% | 0.989 | Multi-generator forensic benchmark |
| Hard Real-World Set | 215 | 92.6% | — | Complex lighting, filters, screenshots |
| AI Video Frames | 20 | 90.0% | — | Modern video-generator output |
| Classic GAN Faces | 25 | 92.0% | — | Synthetic-face-style benchmark |
| Compressed Social Media | 400 | 63.2% | 0.653 | Heavily re-encoded content (active improvement) |
Index Invariant Vectors
Explore the four distinct algorithmic pillars that contribute to the Hypotenuse operational trust index.
Cross-Generator Benchmark Index
Evaluates multi-generator forensic generalization across unseen AI synthesis tools and generative models (AUC 0.989).