Engineering-driven adversarial evaluation and safety training for the world's most capable foundation models. We help Silicon Valley startups and global AI labs secure their systems against real-world threats.
Our security researchers go beyond simple prompts to map the entire latent risk space of your model.
Identifying character-level perturbations and gradient-based suffixes that can trigger prohibited responses by bypassing semantic safety layers.
Probing the model's ability to reconstruct harmful instructions from non-harmful atomic components through multi-turn, high-reasoning interactions.
Stress-testing model weight boundaries to ensure that pre-training data memorization does not leak sensitive or personally identifiable information.
We don't just find bugs; we help you build a fortress. Our reporting is structured to meet the most demanding regulatory and enterprise safety requirements.
Fully aligned with NIST 100-1 guidelines for secure generative AI deployment.
Providing the technical evidence required for high-risk system conformity assessments.
High-level summary for board and legal review.
Complete prompt/response traces for engineering teams.
Tactical instructions for fine-tuning and guardrail hardening.
Common inquiries regarding our adversarial evaluation methodologies and secure data protocols.