slug: tenyks
provider: Tenyks
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: 1
edges:
- tag: Data Upload
  spec_file: tenyks-data-upload-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.8
  evidence: '"POST .../model_inferences  createModel  Create a Model"; "PUT .../model_inferences/{model_key}/predictions  uploadModelPredictions  Upload
    Model Predictions"; vendor: "MLOps monitoring and validation platform"'
  reason: Creating models and ingesting annotations and model predictions for computer-vision model evaluation
    is squarely ML model lifecycle / MLOps tooling, mapped to Artificial Intelligence Management. Some
    residual ambiguity because the surface is also a data-ingestion pipeline.