Robustness where the stakes are highest
The same rigorous adversarial testing, tuned to what you actually operate, from an enterprise CI pipeline to an autonomous system flying over open terrain.
Enterprise AI
Fraud, moderation, biometrics, and document models ship to production without ever being tested against malicious cyber threats. Robustness regressions slip through CI unnoticed, and there is no evidence of resilience when auditors ask for it.
- Automated red-team campaigns wired into your CI
- Per-attack success rates trended across releases
- Adversarial-training corpora and certified-robustness export
- Audit-ready reports mapped to OWASP LLM and NIST AI RMF
Critical Infrastructure
Vision, sensor, and anomaly detection models watch grids, ports, pipelines, and facilities. A threat actor who can nudge an input can shut down a power grid or quiet an alarm, with consequences that are physical, not just digital.
- Detection-proxy hardening for deployed vision pipelines
- Input fingerprinting and feature-squeezing at the edge
- Continuous robustness monitoring with drift alerts
- Deployment that keeps sensitive data inside your boundary
Autonomy & Aerospace
Overhead and airborne perception, the models steering drones, aerial analytics, and autonomous platforms, face physically-realizable attacks that survive altitude, angle, and lighting. These never appear in an accuracy benchmark, and almost no one tests for them. They protect systems the country increasingly relies on.
- Evaluation that mirrors real operating and viewing conditions
- Tiled, oriented-box detection tuned for overhead imagery
- GPS-denied and sensor-spoofing stress tests for drone autonomy
- Secure, on-premise deployment where it's required