Independent AI risk audits and safety engineering for organizations deploying high-risk AI in regulated environments.
Human authority enforced · Uncertainty quantified · Audit-ready documentation
This audit is the required first control for regulated or high-stakes AI deployments. We do not optimize models. We determine whether deploying the system is defensible.
Our services are designed for regulated, high-stakes AI deployments
An AI system is approaching deployment in a regulated environment
A board or executive committee requires independent risk validation
A contract, partnership, or procurement requires AI accountability evidence
A regulator, auditor, or investor asks: "Who is accountable for this system?"
An internal team cannot confidently answer: "What happens if the model is wrong?"
Exploratory research or model prototyping
Implementation or model optimization services
Unregulated, low-impact AI use cases
If AI decisions affect safety, liability, or regulatory exposure, delaying independent review increases organizational risk.
Research, evaluation, and safety engineering across the AI deployment lifecycle
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Bayesian inference frameworks, causal analysis, and information-theoretic diagnostics for rigorous AI evaluation.
Review Publications →
Task-specific metrics, dataset-aware validation, and uncertainty reporting protocols that meet regulatory standards.
Review Methods →
Research prototypes and production deployments with continuous monitoring and feedback loops for ongoing safety.
Assess Solutions →
Attention visualization, feature attribution, and counterfactual analysis for complete model understanding.
Review Details →Every engagement we take on is guided by a single operating principle: safety-critical AI must be held to the highest standard of scrutiny before it reaches the real world.
We build systems where assumptions, evaluation, and operational constraints are explicit.
Our work focuses on safety engineering, uncertainty reporting, and transparency so organizations can make defensible decisions about when and how AI should be used.