A deterministic, four-phase methodology designed to stress-test foundation models, uncover latent logic flaws, and guarantee enterprise-grade deployment safety.
Our process bridges the gap between automated scaling and specialized human insight.
We initiate by securely integrating with your model's API or containerized instance. All evaluations occur within an isolated, air-gapped Virtual Private Cloud (VPC) to ensure absolute weight and data security. We define the evaluation taxonomy alongside your engineering team.
Before human intervention, we run high-throughput automated sweeps. This involves subjecting the model to thousands of deterministic tests to identify high-level statistical failure rates and context-window degradation at scale.
The critical human-in-the-loop phase. We deploy our network of PhDs and domain experts to manually probe the model's logic. Using sophisticated, multi-turn adversarial prompts, we test for 'System 2' reasoning failures and latent space jailbreaks.
We synthesize the findings into a comprehensive Assessment Report detailing exact False Positive Rates (FPR), vulnerability categories (CVE/CWE), and reasoning traces. We also export corrected pairs as pristine SFT training data.
Evaluating frontier models requires extreme operational security. We guarantee zero data retention post-audit.
Every evaluator in our SME network operates under severe, legally-binding Non-Disclosure Agreements.
For highly sensitive models, our red-teamers log into client-provided secure virtual environments. No proprietary weights leave your infrastructure.
Integrate the Acadify verification pipeline into your deployment lifecycle to guarantee reasoning integrity and alignment.