Fibonacci + Risk: quantitative AI for regulated decisionsExplore the scenario library

Security and governance

Controls that begin before the model ships.

Deployment, access, evidence, validation, and release governance are designed into the delivery scope.

Private by default. Auditable by design.

Deployment boundaries

Dedicated tenant or agreed private deployment, separated environments, and controlled connectivity.

Administrator access

No public signup. Customer administrators invite and manage authorized employees.

Identity and roles

Enterprise identity integration, least-privilege roles, and separation of development, validation, and approval.

Evidence retention

Model artifacts, tests, approvals, lineage, decisions, and overrides retained against the applicable version.

Release governance

Defined acceptance criteria, challenger evidence, model sign-off, and controlled promotion to production.

Operational assurance

Monitoring, incident pathways, change records, recovery planning, and agreed service responsibilities.

Acceptance is a deliverable.

Security, validation, risk, and business owners receive evidence aligned to the agreed model and deployment scope.

Model documentation

Purpose, scope, assumptions, limitations, data, features, methods, and intended use.

Validation evidence

Performance, stability, sensitivity, drift, bias, explainability, and challenger results where applicable.

Control evidence

Access, environments, approvals, changes, monitoring, overrides, and operational responsibilities.