slug: segmind
provider: Segmind
generated_by: planning/capability-mapping/scripts/classify_capabilities.py
model: claude-opus-5
frame:
- Electrical Components & Equipment
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: Fine-tuning
  spec_file: segmind-fine-tuning-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.85
  evidence: POST /finetune/request/submit  submitFinetune  Initiate a fine-tuning job; downloadFinetuneFile  Download
    trained model weights
  reason: Submitting fine-tuning jobs, managing training data upload, model access and trained weights
    is ML model lifecycle management (AI/ML model lifecycle, MLOps).
- tag: Inference
  spec_file: segmind-inference-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.8
  evidence: POST /v2/{model_name}  invokeModelAsync  Asynchronous model inference
  reason: Synchronous and asynchronous invocation of AI models plus job status/result retrieval is AI
    model serving — part of the AI/ML model lifecycle capability.