Enterprise Spoof Tester
Detect GAN-generated synthetic health data instantly. Watch the physics engine verify raw signals and generate Zero-Knowledge Proofs for clinical and insurance SLAs.
Adjust sensor values and click verify
Ltotal = Ldata + λ × Lphysics
Ready for Production? Prove the origin and physics of your users' health data to prevent fraud. Cost per verification: $0.005.
Access Enterprise APIThis demo connects to our live Hybrid Proof Engine backend. It takes the parameters you define in the left panel and attempts to pass them through physical verification models.
Step 1: Fast Screening
FNO Speed Engine
Data is initially passed through our Fourier Neural Operator (FNO) which runs in <0.1ms. It detects obvious anomalies immediately without computationally expensive math.
Step 2: Deep Verification
PINNs Architecture
If questionable data is detected, it is routed to our Physics-Informed Neural Networks. The dataset must strictly adhere to known thermodynamic and cardiovascular ODEs (Ordinary Differential Equations) or it will be rejected as mathematically impossible.
Step 3: Cryptographic Finality
ZK Proof Generation
Once the physics simulation passes, we generate a Zero-Knowledge Proof (ZK-SNARK) utilizing EZKL infrastructure. This proof can be trustlessly verified natively on the blockchain to enable automated token rewards.
Try adjusting Heart Rate arbitrarily high without increasing Body Temp. The physics constraints will reject it.