slug: landingai
provider: Landing.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: 2
edges:
- tag: Training
  spec_file: landingai-training-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.85
  evidence: POST /v1/projects/{project_id}/train "Create Training Job"; "Get Training Status"; "Get Confusion
    Matrix For All Splits"; schemas ConfusionMatrix, ClassMetrics
  reason: Model training job creation, architecture selection, train/val splits and evaluation metrics
    are squarely AI/ML model lifecycle (MLOps) operations.
- tag: Model
  spec_file: landingai-model-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.78
  evidence: GET /v1/projects/{project_id}/models "Get Models"; POST /v1/projects/{project_id}/models/{model_id}/download
    "Get Model Download Url"; schemas ModelItem, ModelDownload
  reason: Operations list, inspect and export trained ML models from a vision project, which is plainly
    ML model lifecycle management (AI/ML, MLOps). Not quite 0.95 as the surface is read/download only,
    covering part of the model lifecycle.