A purpose-built security platform for every stage of your AI model lifecycle — from pre-deployment testing to continuous production monitoring.
Each capability works independently or as part of a unified audit pipeline.
Track behavioral drift and anomalous outputs across 100+ model endpoints continuously.
Run 2,400+ automated attack scenarios against deployed models before and after updates.
Auto-generate evidence packages for SOC 2, ISO 42001, and EU AI Act requirements.
Quantify model exposure using a 5-dimension risk score updated on every inference cycle.
Map every API consumer to model access tiers; flag unauthorized or excessive privilege grants.
Trigger automated rollback, alert routing, and forensic logging within 90 seconds of anomaly detection.
NeuralVault integrates at the inference layer, not the perimeter, giving you signal at the model level.
The NeuralVault audit engine connects to your inference endpoints via REST API or native SDK. All probe traffic, behavioral signals, and compliance events flow through a centralized analysis pipeline and surface in the unified dashboard.
Native connectors for the frameworks and platforms your team already uses.
| Specification | Value |
|---|---|
| Supported ML frameworks | 14 (PyTorch, TensorFlow, JAX, Scikit-learn, and more) |
| Attack scenario library | 2,400+ adversarial probes across 8 attack categories |
| Average audit cycle time | Under 4 minutes (full scan, no sampling) |
| Anomaly detection latency | Under 90 seconds from inference event to alert |
| Compliance frameworks | SOC 2 Type II, ISO 42001, EU AI Act, NIST AI RMF |
| Data residency options | US, EU, APAC (enterprise tier) |
| API authentication | OAuth 2.0, API keys, SAML SSO (enterprise) |
| Log retention | 7 days (Starter), 90 days (Professional), unlimited (Enterprise) |
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