Stop Guessing
at AI Risk
Quantify AI risk exposure in monetary terms. AI agents assist with risk identification and scoring, all connected to mitigating controls.
Request a DemoWhy Traditional AI Risk Assessment Falls Short
Qualitative methods can't answer the questions leadership is asking.
Qualitative and stale assessments
"High/Medium/Low" doesn't cut it when the board asks what your actual exposure is. And by the time the assessment is done, it's already outdated.
No portfolio view
Risk assessed per-project, but nobody sees the aggregate exposure across all AI systems.
Disconnected from controls
Risks identified but no clear link to what's actually mitigating them.
Audit trail gaps
Risk decisions made in meetings with no documentation of rationale or methodology.
Quantify, scope, and prove every AI risk
Score AI risks in monetary terms. Hold them inside organization-wide limits. Map each one to the controls and evidence that mitigate it.
Top quantified risks
Every risk scored in monetary terms via Monte Carlo, scenario analysis, or manual entry. Bar height is € exposure.
Quantify risk in monetary terms
Express AI risk exposure in EUR, CHF, or USD. Four methods, one ledger of quantification runs, including the Fermi Risk Agent, our AI-native flagship. Modulos explicitly does not treat risk matrices as quantification.
- 15.05.26€517KRisk Agent · Fermianchored on E-12 records exposed · 2 controls
- 11.05.26€41KMonte Carlo
- 08.05.26€34KRisk Agent · Fermianchored on MCF-4 active users · 3 controls
- 06.05.26€6.7KManual entry
Risk Appetite & Limits
Hierarchical limits (organization, project, category) that sum to 100% of total appetite. Inconsistent limits block quantification until corrected.
Risk value over time
Set a cadence (weekly, monthly, custom) and Modulos re-quantifies every risk in the project. Stable inputs reuse prior assumptions, so the trend reflects real change, not noise.
Threat vector tracking
Each vector traces to its canonical reference: OWASP LLM, EU AI Act, NIST. Add your own.
Risk → Control → Evidence
Automated Risk Quantification
Point the Risk Agent at any risk. It inspects your code, logs, controls, and evidence, then produces a justified monetary estimate. Schedule it to run weekly — get a risk trend, not a risk snapshot.
Investigate
Pulls structural data from your projects — users, revenue, data volumes, frameworks mapped
Audit
Maps existing controls to threats and calculates a mitigation factor from your evidence and test results
Quantify
Runs Fermi estimation using platform data and industry benchmarks to produce a monetary risk value
Justify
Delivers a full analysis breakdown with sources, methodology, and reasoning you can hand to an auditor
Every run is logged with full reasoning. When the agent can't quantify, it tells you exactly what data is missing — no made-up numbers.
Four Pillars. One Platform.
Discover more about the other pillars: Governance, Compliance and AI Agents.
Governance
Run AI governance like an operating system
Project dashboards, AI lifecycle tracking, ownership workflows, and complete audit trails.
Compliance
Multi-framework compliance without duplicate work
One control satisfies many frameworks. Evidence browser with full audit trail.
Agents
Human-in-the-loop AI agents for GRC work
Scout Assistant, evidence automation, control assessments — all with human oversight.
See Risk Quantification in Action
Book a demo to see how Modulos transforms AI governance from a compliance burden into a strategic value driver.