Making AI Safe and Secure
Deploy provably safe and fair AI with automatic verification and robustification
Our solutions
Verification
- Correctness guarantees
- Detect proven adversarial examples
Robustification
- Automatically robustify models
- Version builds and performance metrics
Pipeline Integration
- CI/CD integration
- Automate, build, verify with continuous monitoring and alerts
Build robust, safety critical models
01
Upload Model
Support for wide range of models trained with standard frameworks (PyTorch, TensorFlow, etc).
02
Define Safety Cases
Expressive specifications, including model robustness, expressing noise patterns, bias-field and more. Support for custom, user defined specifications.
03
Verify the Model
Patented, research-based, state-of-the-art verification methods for maximal scalability and efficiency on large models.
04
Apply Robustification
State-of-the-art robustification methods for automatically improving model robustness without additional data.
05
Continuous Analysis and reports
Get continuous performance reports and analytics over model iterations for quality control and guidance in future development.
06
Private Cloud
Fully deployed on-premise or private cloud to avoid any IP leakage.
