slug: viam provider: Viam generated_by: planning/capability-mapping/scripts/classify_capabilities.py model: claude-opus-5 frame: - Automotive & Mobility 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: 7 edges: - tag: Training Jobs spec_file: viam-training-jobs-api-openapi.yml capability_id: BC-610.60 capability_id_l1: BC-610 capability_name: Artificial Intelligence Management confidence: 0.85 evidence: '''Submit, monitor, and manage cloud-hosted ML training jobs that produce models deployable to viam-server''; ''SubmitTrainingJob''' reason: Operations submit, monitor, cancel and delete ML training jobs and retrieve their logs — squarely AI/ML model lifecycle and MLOps management. - tag: OAuth Apps spec_file: viam-oauth-apps-api-openapi.yml capability_id: BC-4270.40 capability_id_l1: BC-4270 capability_name: Developer Identity & Credential Management confidence: 0.78 evidence: '"Viam Create Oauth App", "Viam List Oauth Apps"' reason: Registration and listing of OAuth client applications for the platform, which is issuance and stewardship of developer OAuth clients under Developer Identity & Credential Management. recovered_from: sweep-20260829T005356Z-edges.json - tag: Charges spec_file: viam-charges-api-openapi.yml capability_id: BC-4250 capability_id_l1: BC-4250 capability_name: Subscription Billing & Revenue Management confidence: 0.75 evidence: POST /viam.app.v1.BillingService/CreateInvoiceAndChargeImmediately — Viam Create Invoice And Charge Immediately; 'Retrieve current-month usage, invoice summaries, invoice PDFs, billing tiers' reason: BillingService operations charge an organization and create invoices from metered usage — recurring/usage-based billing for the SaaS platform. L1 clear; ambiguous between invoicing (.30) and payment collection (.40), so no L2. - tag: Billing Tiers spec_file: viam-billing-tiers-api-openapi.yml capability_id: BC-4240 capability_id_l1: BC-4240 capability_name: Subscription Lifecycle Management confidence: 0.7 evidence: POST /viam.app.v1.BillingService/GetAvailableBillingTiers getAvailableBillingTiers; POST /viam.app.v1.BillingService/UpdateOrganizationBillingTier updateOrganizationBillingTier reason: These BillingService operations expose the catalogue of available plan tiers and change which tier an organization is on, plus which organization is billed for a location. That is commercial plan/subscription lifecycle management for the SaaS platform. L2 left null because the evidence straddles Plan & Entitlement Design (tier catalogue) and Subscription Modification (updating an org's tier). recovered_from: sweep-20260829T005356Z-edges.json - tag: Inference spec_file: viam-inference-api-openapi.yml capability_id: BC-610.60 capability_id_l1: BC-610 capability_name: Artificial Intelligence Management confidence: 0.7 evidence: '''Run cloud-hosted inference against models registered in the Viam ML registry''; MLInferenceService/GetInference' reason: Serving ML models registered in a model registry is part of the AI/ML model lifecycle (MLOps), which maps to Artificial Intelligence Management. Single narrow operation keeps confidence moderate. - tag: Invoices spec_file: viam-invoices-api-openapi.yml capability_id: BC-4250.30 capability_id_l1: BC-4250 capability_name: Invoicing & Statement Management confidence: 0.7 evidence: POST /viam.app.v1.BillingService/GetInvoicesSummary Viam Get Invoices Summary; GetInvoicePdf; SendPaymentRequiredEmail reason: Operations retrieve invoice summaries and invoice PDFs and trigger payment-required notifications for a usage-based cloud platform — i.e. invoicing/statement delivery within the subscription billing model, not general ledger accounting. - tag: ML Model spec_file: viam-ml-model-api-openapi.yml capability_id: BC-610.60 capability_id_l1: BC-610 capability_name: Artificial Intelligence Management confidence: 0.7 evidence: Run device-side inference against deployed ML models (TFLite, ONNX, Triton) and inspect model input/output schemas via Metadata reason: Operations Infer and Metadata serve deployed ML model execution and introspection, which sits within AI/ML model lifecycle and MLOps capability.