Shared Risk Language
A clear taxonomy and scoring model everyone can use.
AI introduces new failure modes—prompt injection, data leakage, tool abuse, model drift—and amplifies old ones like privacy exposure and vendor dependency. Forgepath turns these into structured, comparable risks: we define a shared taxonomy, run consistent assessments, and connect each risk to controls, owners, and KRIs. The outcome is a living register, not a shelf document—one that guides decisions across product, engineering, legal, and security.
Our approach is framework-aware (e.g., NIST AI RMF, ISO/IEC 42001, sector expectations) yet tailored to your environment. We capture system inventories and data flows, score likelihood and impact (including potential harms), select safeguards that fit your stack, and establish an operating rhythm for reviews, exceptions, and reporting.
A clear taxonomy and scoring model everyone can use.
Comparable evaluations across AI use cases and vendors.
Safeguards mapped to owners, timelines, and acceptance criteria.
KRIs and dashboards that show whether risk is trending down.
Scorecards and expectations that reduce third-party surprises.
Reviews, exceptions, and reporting that keep the program moving.