Enterprise AI Governance That Actually Works
Join the organizations that turned governance from a blocker into an enabler. Full visibility, continuous risk testing, and compliance proof — on autopilot.
Get a Demo
Recognized by
When we assess an AI system for risk, we do not look at it as a single score or a pass/fail check. We evaluate risk across six distinct dimensions, each one looking at a different way the system could fail, cause harm, or create exposure for your organization.
Together, these six dimensions give you a complete view of your AI system's risk profile. They are built into every layer of our platform - from Risk Mapping to individual assessments to compliance reporting.
Bias evaluates whether your AI system treats different groups of people fairly. AI systems can inherit or amplify bias from training data, design choices, or the way they are deployed - leading to unfair outcomes for certain demographic groups.
Our Bias assessments look at how your system performs across different populations and whether it produces outcomes that could be considered discriminatory. This includes both qualitative evaluations of your system's design and quantitative analysis of its actual outputs.
Learn more in What is a Bias Assessment?
Robustness measures how reliably your AI system performs when conditions change. This includes handling unexpected inputs, operating in new environments, dealing with noisy or incomplete data, and resisting adversarial attacks designed to manipulate its behavior.
A robust system continues to produce reliable results even when things do not go exactly as expected. Our Robustness assessments check whether your system can withstand real-world variability without failing or producing harmful outputs.
Learn more in What is a Robustness Assessment?
Transparency looks at whether your AI system's behavior can be understood, explained, and traced. Stakeholders - from regulators to business leaders to end users - need to understand why an AI system made a particular decision or produced a specific output.
Our Transparency assessments evaluate whether your system has sufficient documentation, whether its decision-making process can be explained, and whether there is a clear audit trail from input to output.
Learn more in What is a Transparency Assessment?
Privacy evaluates how your AI system handles personal, sensitive, or confidential data. This covers the entire data lifecycle - from what data goes into the system, how it is processed, what the system stores, and what it outputs.
With data protection regulations becoming more stringent globally, understanding privacy risk is critical. Our Privacy assessments identify areas where your system may expose personal data, lack appropriate controls, or fall short of regulatory expectations.
Learn more in What is a Privacy Assessment?
Efficacy assesses whether your AI system actually works as intended. A system can be fair, robust, transparent, and privacy-compliant - but if it does not deliver accurate, useful results, it still creates risk for your organization.
Our Efficacy assessments look at whether the system's outputs are relevant, complete, and aligned with the defined use case. An ineffective AI system wastes resources, erodes trust, and can lead to poor decision-making downstream.
Learn more in What is an Efficacy Assessment?
Exposure evaluates how likely it is that identified risks will actually be triggered in the real world. A system with a bias issue that is only used internally by a small team has a very different risk profile than one with the same issue deployed to millions of external users.
Our Exposure assessments look at deployment context, user access, interaction volume, and how the system fits into broader business processes. This helps your team prioritize - focusing resources on the risks that are most likely to cause real impact.
Learn more in What is an Exposure Assessment?
No single dimension tells the whole story. A system might score well on Bias but poorly on Transparency. It might be highly effective but have significant privacy concerns. The power of our approach is that you see all six dimensions together, so your team can make informed decisions about where to invest in mitigation and what level of risk is acceptable for each system.
All six dimensions are evaluated during Risk Mapping and can be explored individually through our dedicated assessment tools. Results feed directly into your AI governance workflows, compliance reports, and mitigation plans.