slug: tensorflow
provider: TensorFlow
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: 2
edges:
- tag: Inference
  spec_file: tensorflow-inference-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.8
  evidence: TensorFlow ModelServer supports REST APIs for model status checks, metadata retrieval, classification,
    regression, and prediction inference
  reason: The operations serve trained ML models for classification, regression and prediction inference
    in production, including versioned model endpoints. This is the serving/MLOps leg of AI/ML model lifecycle
    management (BC-610.60); some ambiguity only because it is runtime inference rather than the full lifecycle.
- tag: Models
  spec_file: tensorflow-models-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.8
  evidence: '"TensorFlow ModelServer supports REST APIs for model status checks, metadata retrieval, classification,
    regression, and prediction inference"; operations "Get Model Status", "Get Model Version Metadata"'
  reason: Operations expose status and metadata of deployed machine-learning models in a production serving
    system, which is ML model lifecycle / MLOps work under Artificial Intelligence Management. Not a product-engineering
    or tenant capability — the objects are ML models, not software releases.