Quantify AI risk the way your business actually experiences it.
A leaked financial report means something very different to a bank than to a company whose financial data is mainly billing. Generic risk scores ignore that, so teams cannot tell what really matters.
GRCortex AI runs the full AI risk lifecycle - discover, inventory, quantify, assess, register, track and calculates residual risk based on the nature and purpose of your business. Its risk library describes known risks and how to measure them, your configuration decides how much each one hurts you.
Risk: Financial report leaked by AI
High impactRisk: Financial report leaked by AI
Lower impactIllustrative sample data
AI risk is usually either not measured at all or measured with one-size-fits-all scores that do not reflect business impact.
No consistent way to quantify AI risk in business terms.
Risk assessments are manual and disconnected from security testing.
Teams cannot separate real risks from false positives.
Open, resolved and residual risk are not tracked in one place.
Impact is scored across five dimensions - financial, reputational, regulatory, operational and human and you set the thresholds that matter to your business.
Controls are measured across technical, governance, process and human oversight foundations.
The platform combines impact and control effectiveness to calculate residual risk for every AI application.
A growing library of known risks, and how to measure them, and best-practice controls, used to judge whether a finding is a real risk.
Findings arrive automatically from HexaShield AI, and teams can also run assessments and evals - for example for bias, misinformation or sensitive information disclosure.
Find AI applications and build the AI-BOM.
Tune the scoring model to your business: impact dimensions and control effectiveness.
Combine HexaShield findings with assessments and evals.
Use the risk library to separate real risks from false positives.
Record residual risk, open and resolved risks and current score in the AI risk register.
Follow mitigations and reassess as AI changes.
A bank runs a loan assistant. Security testing shows a prompt injection can expose customers' personal data.
GRCortex AI assesses the finding against the bank's configured model. Because this is a lending application, financial, reputational and regulatory impact are all high. Existing controls are rated for technical, governance, process and human oversight effectiveness.
The platform calculates a high residual risk and places it at the top of the AI risk register with an owner and mitigation status. The same weakness in a low-impact internal tool would score lower - so effort goes where it matters.
AI risk scored against the impact that matters to your organization.
Library-based validation separates real risk from noise.
Open, resolved and residual risk tracked together.
Risk is reassessed as AI and threats change.
Quantified, business-relevant AI risk.
Security findings translated into residual risk.
A repeatable lifecycle for every AI application.
A traceable record of how each risk was assessed.
Discover, quantify, assess and track AI risk in business terms: financial, reputational, regulatory, operational and human impact.
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