Default Implementation

A lifecycle automation for standard model implementations that performs completeness checks, runs Standard Risk Tests, collects approvals, and marks the model as deployed in validation and production environments.

All Terms
Risk Scoring Engine
AI Governance
AI Governance Score
AI Lifecycle Automation
AI Policy
AI Risk
AI Use Case
AI/ML Operationalization
AIMS
AUC
Abstraction
Alerting Rules
Annual Review
Artifact Versioning
Asset
Associated Model
Assurance
Attestation
Audit Compliance Layer
Audit Trail
Automated Model Validation
Autonomous System
Bias
Bias Monitor
Black Box AI
Brand Risk
CI/CD for Models
Capability Maturity Assessment
Center of Excellence (CoE)
Champion-Challenger Testing
Conformity Assessment
Confusion Matrix
Containerization
Data Drift
Data Scientist
DataOps
Decision Table
Default Implementation
Deployment
DevOps
Disparity Metric
Distillation (Model Distillation)
EU AI Act
Encapsulation
Enterprise AI
Enterprise AI Architect
Environment Promotion
Environment/Stage Tagging
Evaluation Metric
Event-Driven Workflow Automation
Expert Model
Explainability
F1 Score
Fairness
Foundational Model
Heterogeneous Analytics Ecosystem
Human-in-the-Loop (HITL)
ITOps
Inferences
Interpretability
LOB Analyst
LOB Executive
Lineage
Loss Model
MLOps
Machine Learning
Metadata-Driven Automation
Metric Function
Metrics Job
Model
Model Card
Model Debt
Model Decay
Model Drift
Model Governance
Model Inventory
Model Lifecycle Management
Model Risk Management
Model Service Tag
ModelOps
ModelOps Engineer
Monitoring SDK
Operational Assurance
Operationalization
Policy-as-Code (PaC)
Portfolio Intelligence
Predictions
Predictive Models
Process Automation
Production Process Controls
Production Setting
Programmatic RAI Assessments
ROC Curve
Required Assets
Reward Model
Runtime
SHAP Values
Schema
Scoring Job
Shadow AI