Kovral's risk engine runs continuously across your AI deployment, identifying and scoring risks before they become incidents.
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Risk Register
A live register of every identified AI risk in your organisation — model-level, use-case-level, and organisational. Each entry includes risk description, likelihood, impact, owner, and remediation status.
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Risk Scoring
Each risk is scored on a 1–25 scale (5×5 likelihood × impact matrix). Scores are recalculated automatically as your environment changes — a new model deployment or policy gap triggers a re-score.
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Risk Prioritisation
Kovral prioritises risks by a combination of score, exploitability (is there an active threat actor targeting this vector?), and regulatory relevance (does this risk create a compliance gap?).
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Remediation Guidance
Each risk entry includes specific remediation steps, a recommended policy change, or a Kovral feature that directly addresses the risk — linked to the relevant compliance control.
Risk Frameworks
Aligned to Industry Standards
Kovral's risk taxonomy is aligned to NIST AI RMF, ISO 42001, and the EU AI Act risk classification system.
140+
AI risk scenarios in Kovral's risk library
5
major frameworks: NIST AI RMF, ISO 42001, EU AI Act, SOC 2, HIPAA
24h
SLA for risk assessment after a new model deployment
FAQ
Common Questions
Traditional cybersecurity risk focuses on CIA (Confidentiality, Integrity, Availability) threats to IT systems. AI risk includes these but adds categories unique to AI: model manipulation (prompt injection, adversarial attacks), output risk (hallucinations, bias, harmful content), data risk (training data contamination, privacy leakage), autonomy risk (agent goal drift, unintended actions), and compliance risk (regulatory non-conformity with AI-specific regulations like the EU AI Act). Kovral's risk engine covers all categories.
Yes. Kovral integrates with major GRC platforms (ServiceNow GRC, Archer, OneTrust, Vanta, Drata, Secureframe) via REST API and webhook. Risk findings, compliance gaps, and evidence collected by Kovral can be pushed to your GRC platform automatically, keeping your enterprise risk register current without manual exports. For platforms without a native integration, Kovral supports generic webhook and CSV export.
Risk entries can be marked as "accepted" by an authorised approver with a documented rationale and review date. Accepted risks are removed from the active remediation queue but remain visible in the risk register with their acceptance context. Kovral sends a reminder when the review date approaches. Accepted risks are flagged in compliance reports so auditors can see the acceptance decision and its documentation.
An AI risk assessment is a structured review of your organisation's AI deployment against a defined risk taxonomy. Kovral performs this continuously and automatically — not as a periodic manual exercise. When a significant change occurs (new model deployment, new use case, policy change, regulatory update), Kovral automatically triggers a targeted reassessment of the affected risk areas and updates the risk register within 24 hours.
From Fortune 500 CISOs to fast-growing AI startups — teams protecting AI at scale choose Kovral.
★★★★★
"Kovral gave us our first real-time view into every AI tool running inside our bank. We found 34 unsanctioned models in the first 48 hours. The posture score is now a standing item on my CISO dashboard."
Marcus Reid
VP Security Engineering · Tier-1 Bank
★★★★★
"Our EU AI Act readiness went from 'we don't know' to a documented compliance posture in three weeks. The use case registry and automated evidence collection saved our team months of manual work."
Priya Nair
Chief Compliance Officer · HealthTech SaaS
★★★★★
"The AI Firewall blocked a live indirect prompt injection attack on our customer-facing agent within the first week of deployment. Zero code changes, 1.8ms added latency. It's the easiest security win I've had in years."
