slug: voyage-ai
provider: Voyage 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: 3
edges:
- tag: Contextualized
  spec_file: voyage-ai-contextualized-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.7
  evidence: POST /contextualizedembeddings  "Create contextualized chunk embeddings"; "REST API for Voyage
    AI embedding and reranker models used in retrieval-augmented generation (RAG) and semantic search
    workflows"
  reason: Model inference endpoint producing embeddings for RAG/semantic search. The honest mapping for
    an AI model-serving devtool is Artificial Intelligence Management; it is inference rather than full
    model lifecycle, hence moderate confidence.
- tag: Embeddings
  spec_file: voyage-ai-embeddings-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.7
  evidence: POST /embeddings  createEmbeddings  "Create text embeddings"
  reason: Text embedding model inference used for retrieval and semantic search; falls under AI/ML capability
    in Information & Data Management. No industry-specific business process is realised.
- tag: Multimodal
  spec_file: voyage-ai-multimodal-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.7
  evidence: POST /multimodalembeddings  "Create multimodal embeddings (text + images)"
  reason: Multimodal embedding model inference — AI model capability, not a domain business process.