slug: google-vertex-ai
provider: Google Vertex AI
generated_by: planning/capability-mapping/scripts/classify_capabilities.py
model: claude-opus-5
frame:
- Software & Technology
min_confidence: 0.7
capability_model:
  source: https://github.com/vincentmakes/turbo-ea-capabilities
  license: CC-BY-4.0
  attribution: Turbo EA Capabilities by Vincent Verdet — Turbo EA, https://github.com/vincentmakes/turbo-ea-capabilities,
    CC BY 4.0
  notice: NOTICE
edge_count: 4
edges:
- tag: Models
  spec_file: google-vertex-ai-models-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.85
  evidence: 'listModels / getModel / deleteModel; schemas: Model, ModelList; vendor: "build, deploy, and
    scale ML models"'
  reason: Direct CRUD over the ML model registry of a machine learning platform, which is exactly AI/ML
    model lifecycle and MLOps management. No competing reading of "Models" fits this context.
- tag: Predictions
  spec_file: google-vertex-ai-predictions-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.8
  evidence: POST /projects/{project}/locations/{location}/endpoints/{endpoint}:predict — 'Run a prediction';
    schemas PredictRequest, PredictResponse
  reason: Serving inference from deployed ML models on an ML platform is part of the AI/ML model lifecycle
    (MLOps), which maps to Artificial Intelligence Management under Information & Data Management.
- tag: TrainingPipelines
  spec_file: google-vertex-ai-trainingpipelines-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.8
  evidence: 'GET /projects/{project}/locations/{location}/trainingPipelines — ''List training pipelines'';
    description: ''orchestrate ML pipelines on Google Cloud'''
  reason: Model training pipeline orchestration is core AI/ML model lifecycle / MLOps tooling, mapping
    to Artificial Intelligence Management.
- tag: Endpoints
  spec_file: google-vertex-ai-endpoints-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.78
  evidence: 'POST /projects/{project}/locations/{location}/endpoints  createEndpoint  Create an endpoint;
    schemas: Endpoint, EndpointList, Operation'
  reason: Vertex AI endpoints are model-serving deployment targets, i.e. the MLOps serving stage of the
    AI/ML model lifecycle. Slight ambiguity with generic IT infrastructure provisioning keeps this below
    0.85.