slug: beyond
provider: Beyond
generated_by: planning/capability-mapping/scripts/classify_capabilities.py
model: claude-opus-5
frame:
- Travel & Hospitality
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: Compsets
  spec_file: beyond-compsets-api-openapi.yml
  capability_id: BC-4030.40
  capability_id_l1: BC-4030
  capability_name: Competitive Rate Intelligence
  confidence: 0.85
  evidence: 'GET /api/v1/compsets/{compset_id}/  get_compset  Get a comp set by id; schemas: CompsetPerformance,
    CompsetMemberMetrics'
  reason: Competitive-set definitions with performance metrics on a revenue-management platform whose
    vendor description cites 'competitive-set analysis' — competitive rate and market-position intelligence.
- tag: Customizations
  spec_file: beyond-customizations-api-openapi.yml
  capability_id: BC-4030.20
  capability_id_l1: BC-4030
  capability_name: Pricing & Rate Strategy Management
  confidence: 0.8
  evidence: PATCH /api/v1/listings/{listing_id}/customizations/base-price/  Update base price customization
    for a listing; .../min-max-prices/; .../time-based-adjustments/
  reason: Operations configure base price, price floors/ceilings, seasonal and time-based rate adjustments
    and minimum stays that drive dynamic nightly pricing — definition and adjustment of rate strategy
    for lodging products.
- tag: Listings
  spec_file: beyond-listings-api-openapi.yml
  capability_id: BC-4030
  capability_id_l1: BC-4030
  capability_name: Travel Revenue & Yield Management
  confidence: 0.7
  evidence: GET /api/v1/listings/{listing_id}/recommendations/  "List recommendations for a listing";
    GET /api/v1/listings/{listing_id}/calendar/  "Get calendar for a listing"; schemas Recommendation,
    CalendarEntry, Factor
  reason: Listings here are short-term-rental units whose calendars carry AI-driven pricing recommendations
    — the surface delivers dynamic pricing/yield decisions rather than pure product master data. Kept
    at L1 because the endpoints straddle rate strategy, listing detail and reservation refresh.