slug: together-ai
provider: Together AI
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: 6
edges:
- tag: Fine-tuning
  spec_file: together-ai-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 /fine-tunes Create job; GET /fine-tunes/{id}/checkpoints List checkpoints; GET /fine-tunes/{id}/metrics
    Get metrics
  reason: Training job creation, checkpoints, training metrics and model download constitute ML model
    lifecycle / MLOps, squarely Artificial Intelligence Management.
- tag: RL
  spec_file: together-ai-rl-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.85
  evidence: POST /rl/training-sessions startTrainingSession  Create training session; POST .../operations/optim-step  Optimizer
    step; RL.GRPOLossParams, RL.TrainingCheckpointResult
  reason: Reinforcement-learning training sessions with forward-backward passes, optimizer steps and inference
    checkpoints are squarely ML model training / MLOps, i.e. Artificial Intelligence Management.
- tag: GPUClusterService
  spec_file: together-ai-gpuclusterservice-api-openapi.yml
  capability_id: BC-600.50
  capability_id_l1: BC-600
  capability_name: IT Infrastructure Management
  confidence: 0.8
  evidence: POST /compute/clusters GPUClusterService_Create Create GPU Cluster; schemas GPUClusterControlPlaneNode,
    GPUClusterGPUWorkerNode
  reason: Operations provision, update and delete GPU compute clusters with control-plane and worker nodes
    — this is compute infrastructure provisioning and management, i.e. IT Infrastructure Management, not
    an industry-specific capability.
- tag: SharedVolumeService
  spec_file: together-ai-sharedvolumeservice-api-openapi.yml
  capability_id: BC-600.50
  capability_id_l1: BC-600
  capability_name: IT Infrastructure Management
  confidence: 0.8
  evidence: POST /compute/clusters/storage/volumes  SharedVolumeService_Create  Create a shared volume.
  reason: Provisioning and lifecycle of shared storage volumes attached to compute clusters is storage/cloud
    infrastructure management under IT Infrastructure Management.
- tag: Models
  spec_file: together-ai-models-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.75
  evidence: POST /models uploadModel  Upload a custom model or adapter; schemas ModelInfo, ModelUploadRequest
  reason: Registry and upload of ML models and adapters is model lifecycle / MLOps management, mapping
    to Artificial Intelligence Management.
- tag: evaluation
  spec_file: together-ai-evaluation-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.7
  evidence: POST /evaluation createEvaluationJob Create an evaluation job; schemas EvaluationJudgeModelConfig,
    EvaluationScoreResults
  reason: Jobs that score, classify and compare model outputs with judge-model configuration are model
    evaluation within the AI/ML lifecycle, mapping to Artificial Intelligence Management. Not experimentation
    of a SaaS product feature, so BC-4280 does not fit.