{
  "schema": "aivaon.well-known.category_scoreboard.v1",
  "section": "16.8",
  "version": "16.8.0",
  "last_updated": "2026-04-22",
  "canonical_artifact_path": "backend/artifacts/aivaon-section16.8-category-scoreboard.json",
  "measurement_dimensions": [
    {
      "id": "DIM_COMMERCIAL",
      "name": "Commercial",
      "description": "Commercial traction measures: competitive win rates, ACV trajectory, sales cycle length, expansion revenue (NRR), churn, and competitor displacement. Converts product-market fit and category definition into sustained commercial outcome.",
      "metric_count": 7,
      "owner": "OWN_CEO",
      "review_cadence_days": 7,
      "linked_pillars": [
        "PILLAR_CATEGORY_NARRATIVE",
        "PILLAR_UNIT_ECONOMICS"
      ]
    },
    {
      "id": "DIM_PRODUCT",
      "name": "Product",
      "description": "Product activation + adoption measures: time-to-first-call (90s target), time-to-production (30m target), integration success rate, template deployment rate, continuity feature adoption, on-device hybrid intelligence usage. Converts the §16.2 product catalog into live productive-use evidence.",
      "metric_count": 6,
      "owner": "OWN_CPO",
      "review_cadence_days": 14,
      "linked_pillars": [
        "PILLAR_PLATFORM_BREADTH",
        "PILLAR_HYBRID_INTELLIGENCE",
        "PILLAR_ECOSYSTEM_BREADTH"
      ]
    },
    {
      "id": "DIM_TECHNICAL",
      "name": "Technical",
      "description": "Technical performance measures: call setup latency P50/P95/P99 per cell, end-to-end conversational latency including barge-in response, session failure rate, model routing success, infrastructure cost per minute, uptime per cell and jurisdiction against SLA. The substrate evidence that supports every commercial + product claim.",
      "metric_count": 7,
      "owner": "OWN_ENGINEERING",
      "review_cadence_days": 7,
      "linked_pillars": [
        "PILLAR_SUBSTRATE_OWNERSHIP",
        "PILLAR_UNIT_ECONOMICS",
        "PILLAR_MULTI_JURISDICTIONAL"
      ]
    },
    {
      "id": "DIM_STRATEGIC",
      "name": "Strategic",
      "description": "Strategic positioning measures: analyst mentions (Gartner/Forrester/IDC), named customer case studies, sovereign pipeline, international revenue share, category search growth, and partner ecosystem growth. The leading-indicator set for sustained category leadership.",
      "metric_count": 6,
      "owner": "OWN_CEO",
      "review_cadence_days": 30,
      "linked_pillars": [
        "PILLAR_CATEGORY_NARRATIVE",
        "PILLAR_MULTI_JURISDICTIONAL",
        "PILLAR_ECOSYSTEM_BREADTH",
        "PILLAR_COMPLIANCE_DEPTH"
      ]
    }
  ],
  "metrics": [
    {
      "id": "METRIC_WIN_RATE_VS_WRAPPERS",
      "dimension": "DIM_COMMERCIAL",
      "name": "Win rate vs wrapper platforms (Vapi, Retell, Bland)",
      "description": "Proportion of competitive deals won when the alternative consideration is one of Vapi, Retell, or Bland. Primary mechanic for wrapper-platform displacement.",
      "unit": "percent",
      "direction": "higher_is_better",
      "baseline": 45,
      "targets": {
        "q1": 55,
        "q2": 62,
        "q3": 70,
        "q4": 75,
        "year_2": 80
      },
      "thresholds": {
        "green": 70,
        "yellow": 55
      },
      "data_source_kind": "database",
      "owner": "OWN_CI_LEAD",
      "review_cadence_days": 7,
      "competitor_reference_ids": [
        "COMP_VAPI",
        "COMP_RETELL",
        "COMP_BLAND"
      ],
      "linked_pillar_ids": [
        "PILLAR_CATEGORY_NARRATIVE",
        "PILLAR_SUBSTRATE_OWNERSHIP"
      ],
      "linked_mechanic_ids": [
        "MECH_WIN_RATE",
        "MECH_HYBRID_DIFFERENTIATION"
      ]
    },
    {
      "id": "METRIC_WIN_RATE_VS_HYPERSCALER",
      "dimension": "DIM_COMMERCIAL",
      "name": "Win rate vs hyperscaler-native options (Google Contact Center AI, Microsoft Copilot Studio)",
      "description": "Proportion of competitive deals won when the alternative is a hyperscaler-native voice AI platform. Tests AIVAON's sovereignty + substrate-ownership positioning against cloud-native incumbents.",
      "unit": "percent",
      "direction": "higher_is_better",
      "baseline": 35,
      "targets": {
        "q1": 42,
        "q2": 50,
        "q3": 58,
        "q4": 65,
        "year_2": 72
      },
      "thresholds": {
        "green": 60,
        "yellow": 45
      },
      "data_source_kind": "database",
      "owner": "OWN_CI_LEAD",
      "review_cadence_days": 7,
      "competitor_reference_ids": [
        "COMP_GOOGLE_CCAI",
        "COMP_MS_COPILOT_STUDIO"
      ],
      "linked_pillar_ids": [
        "PILLAR_CATEGORY_NARRATIVE",
        "PILLAR_COMPLIANCE_DEPTH",
        "PILLAR_SUBSTRATE_OWNERSHIP"
      ],
      "linked_mechanic_ids": [
        "MECH_WIN_RATE",
        "MECH_COMPLIANCE_UNLOCK"
      ]
    },
    {
      "id": "METRIC_ACV_TREND",
      "dimension": "DIM_COMMERCIAL",
      "name": "Average annual contract value (ACV) trend",
      "description": "ACV across new logos, trending upward as tier mix shifts toward Business and Enterprise SKUs. Evidence of enterprise-grade positioning taking hold.",
      "unit": "usd",
      "direction": "higher_is_better",
      "baseline": 25000,
      "targets": {
        "q1": 32000,
        "q2": 42000,
        "q3": 55000,
        "q4": 72000,
        "year_2": 120000
      },
      "thresholds": {
        "green": 60000,
        "yellow": 40000
      },
      "data_source_kind": "database",
      "owner": "OWN_CEO",
      "review_cadence_days": 14,
      "linked_pillar_ids": [
        "PILLAR_UNIT_ECONOMICS",
        "PILLAR_PLATFORM_BREADTH"
      ],
      "linked_mechanic_ids": [
        "MECH_NEW_LOGO_ACQUISITION",
        "MECH_EXPANSION_REVENUE"
      ]
    },
    {
      "id": "METRIC_SALES_CYCLE_LENGTH",
      "dimension": "DIM_COMMERCIAL",
      "name": "Sales cycle length",
      "description": "Median days from opportunity creation to close. Trending downward as category definition reduces evaluation complexity.",
      "unit": "days",
      "direction": "lower_is_better",
      "baseline": 120,
      "targets": {
        "q1": 105,
        "q2": 90,
        "q3": 75,
        "q4": 65,
        "year_2": 55
      },
      "thresholds": {
        "green": 70,
        "yellow": 95
      },
      "data_source_kind": "crm",
      "owner": "OWN_CEO",
      "review_cadence_days": 14,
      "linked_pillar_ids": [
        "PILLAR_CATEGORY_NARRATIVE"
      ],
      "linked_mechanic_ids": [
        "MECH_NEW_LOGO_ACQUISITION",
        "MECH_ANALYST_RECOGNITION"
      ]
    },
    {
      "id": "METRIC_NET_DOLLAR_RETENTION",
      "dimension": "DIM_COMMERCIAL",
      "name": "Dollar-based net revenue retention (NRR)",
      "description": "Expansion revenue from existing customers measured as dollar-based net retention. Primary driver of unit-economic sustainability.",
      "unit": "percent",
      "direction": "higher_is_better",
      "baseline": 105,
      "targets": {
        "q1": 110,
        "q2": 115,
        "q3": 120,
        "q4": 125,
        "year_2": 135
      },
      "thresholds": {
        "green": 120,
        "yellow": 105
      },
      "data_source_kind": "database",
      "owner": "OWN_CEO",
      "review_cadence_days": 30,
      "linked_pillar_ids": [
        "PILLAR_UNIT_ECONOMICS"
      ],
      "linked_mechanic_ids": [
        "MECH_EXPANSION_REVENUE",
        "MECH_RENEWAL_HEALTH"
      ]
    },
    {
      "id": "METRIC_CHURN_RATE",
      "dimension": "DIM_COMMERCIAL",
      "name": "Gross logo churn rate",
      "description": "Trailing-12-month gross churn rate. Trending downward as platform integration deepens and customers accumulate switching cost.",
      "unit": "percent",
      "direction": "lower_is_better",
      "baseline": 12,
      "targets": {
        "q1": 10,
        "q2": 8,
        "q3": 7,
        "q4": 6,
        "year_2": 4
      },
      "thresholds": {
        "green": 7,
        "yellow": 10
      },
      "data_source_kind": "database",
      "owner": "OWN_SOLUTIONS",
      "review_cadence_days": 30,
      "linked_pillar_ids": [
        "PILLAR_UNIT_ECONOMICS",
        "PILLAR_PLATFORM_BREADTH"
      ],
      "linked_mechanic_ids": [
        "MECH_RENEWAL_HEALTH"
      ]
    },
    {
      "id": "METRIC_COMPETITOR_DISPLACEMENT_RATE",
      "dimension": "DIM_COMMERCIAL",
      "name": "Competitor displacement rate",
      "description": "Proportion of new deals that replace (rip-and-replace) a named competitor deployment. Leading indicator of the displacement motion that drives sustained category leadership.",
      "unit": "percent",
      "direction": "higher_is_better",
      "baseline": 15,
      "targets": {
        "q1": 22,
        "q2": 30,
        "q3": 38,
        "q4": 45,
        "year_2": 55
      },
      "thresholds": {
        "green": 40,
        "yellow": 25
      },
      "data_source_kind": "database",
      "owner": "OWN_CI_LEAD",
      "review_cadence_days": 14,
      "linked_pillar_ids": [
        "PILLAR_CATEGORY_NARRATIVE"
      ],
      "linked_mechanic_ids": [
        "MECH_WIN_RATE",
        "MECH_BENCHMARK_DISPLACEMENT"
      ]
    },
    {
      "id": "METRIC_TIME_TO_FIRST_CALL",
      "dimension": "DIM_PRODUCT",
      "name": "Signup → first successful call (TTFC)",
      "description": "Median time from signup completion to first successful voice call, p95 measured. Contractual commitment to the 90-second target that defines the §16.7 Phase 2 exit criterion.",
      "unit": "seconds",
      "direction": "lower_is_better",
      "baseline": 180,
      "targets": {
        "q1": 130,
        "q2": 105,
        "q3": 95,
        "q4": 90,
        "year_2": 75
      },
      "thresholds": {
        "green": 90,
        "yellow": 120
      },
      "data_source_kind": "rum",
      "owner": "OWN_ENGINEERING",
      "review_cadence_days": 7,
      "linked_pillar_ids": [
        "PILLAR_SUBSTRATE_OWNERSHIP",
        "PILLAR_PLATFORM_BREADTH"
      ],
      "linked_mechanic_ids": [
        "MECH_NEW_LOGO_ACQUISITION",
        "MECH_DEVELOPER_ECOSYSTEM"
      ]
    },
    {
      "id": "METRIC_TIME_TO_PRODUCTION",
      "dimension": "DIM_PRODUCT",
      "name": "Signup → first production deployment (TTP)",
      "description": "Median time from signup to first production-grade deployment, measured against the 30-minute target. Evidence of self-serve productive-use capability.",
      "unit": "minutes",
      "direction": "lower_is_better",
      "baseline": 90,
      "targets": {
        "q1": 60,
        "q2": 45,
        "q3": 35,
        "q4": 30,
        "year_2": 20
      },
      "thresholds": {
        "green": 30,
        "yellow": 50
      },
      "data_source_kind": "database",
      "owner": "OWN_ENGINEERING",
      "review_cadence_days": 14,
      "linked_pillar_ids": [
        "PILLAR_PLATFORM_BREADTH"
      ],
      "linked_mechanic_ids": [
        "MECH_NEW_LOGO_ACQUISITION",
        "MECH_DEVELOPER_ECOSYSTEM"
      ]
    },
    {
      "id": "METRIC_INTEGRATION_SUCCESS_RATE",
      "dimension": "DIM_PRODUCT",
      "name": "Integration success rate",
      "description": "Proportion of integration activations that reach production use within 14 days. Evidence of Marketplace integration quality.",
      "unit": "percent",
      "direction": "higher_is_better",
      "baseline": 60,
      "targets": {
        "q1": 68,
        "q2": 75,
        "q3": 82,
        "q4": 88,
        "year_2": 92
      },
      "thresholds": {
        "green": 82,
        "yellow": 70
      },
      "data_source_kind": "database",
      "owner": "OWN_ENGINEERING",
      "review_cadence_days": 14,
      "linked_pillar_ids": [
        "PILLAR_ECOSYSTEM_BREADTH"
      ],
      "linked_mechanic_ids": [
        "MECH_INTEGRATION_ADOPTION"
      ]
    },
    {
      "id": "METRIC_TEMPLATE_DEPLOYMENT_RATE",
      "dimension": "DIM_PRODUCT",
      "name": "Template deployment rate",
      "description": "Proportion of customers who deploy from a Studio / vertical-pack template rather than building from scratch. Evidence of template quality + onboarding acceleration.",
      "unit": "percent",
      "direction": "higher_is_better",
      "baseline": 35,
      "targets": {
        "q1": 45,
        "q2": 55,
        "q3": 65,
        "q4": 72,
        "year_2": 80
      },
      "thresholds": {
        "green": 65,
        "yellow": 50
      },
      "data_source_kind": "database",
      "owner": "OWN_SOLUTIONS",
      "review_cadence_days": 14,
      "linked_pillar_ids": [
        "PILLAR_PLATFORM_BREADTH"
      ],
      "linked_mechanic_ids": [
        "MECH_NEW_LOGO_ACQUISITION",
        "MECH_INTEGRATION_ADOPTION"
      ]
    },
    {
      "id": "METRIC_CONTINUITY_FEATURE_ADOPTION",
      "dimension": "DIM_PRODUCT",
      "name": "Continuity feature adoption (ambient voice + memory)",
      "description": "Proportion of active customers who activate ambient voice and memory continuity features. Differentiation adoption signal.",
      "unit": "percent",
      "direction": "higher_is_better",
      "baseline": 18,
      "targets": {
        "q1": 28,
        "q2": 38,
        "q3": 48,
        "q4": 58,
        "year_2": 70
      },
      "thresholds": {
        "green": 48,
        "yellow": 30
      },
      "data_source_kind": "prometheus",
      "owner": "OWN_APPLIED_AI",
      "review_cadence_days": 14,
      "linked_pillar_ids": [
        "PILLAR_HYBRID_INTELLIGENCE",
        "PILLAR_PLATFORM_BREADTH"
      ],
      "linked_mechanic_ids": [
        "MECH_EXPANSION_REVENUE",
        "MECH_HYBRID_DIFFERENTIATION"
      ]
    },
    {
      "id": "METRIC_ON_DEVICE_USAGE",
      "dimension": "DIM_PRODUCT",
      "name": "On-device hybrid intelligence usage",
      "description": "Proportion of sessions that route inference to the on-device WebLLM / Edge runtime rather than managed/self-hosted. Measures the hybrid-intelligence pillar's commercial adoption.",
      "unit": "percent",
      "direction": "higher_is_better",
      "baseline": 15,
      "targets": {
        "q1": 22,
        "q2": 30,
        "q3": 40,
        "q4": 50,
        "year_2": 62
      },
      "thresholds": {
        "green": 40,
        "yellow": 25
      },
      "data_source_kind": "prometheus",
      "owner": "OWN_APPLIED_AI",
      "review_cadence_days": 7,
      "linked_pillar_ids": [
        "PILLAR_HYBRID_INTELLIGENCE"
      ],
      "linked_mechanic_ids": [
        "MECH_HYBRID_DIFFERENTIATION"
      ]
    },
    {
      "id": "METRIC_CALL_SETUP_LATENCY_P50",
      "dimension": "DIM_TECHNICAL",
      "name": "Call setup latency (P50, by cell)",
      "description": "P50 time from carrier offer to media flowing, per cell (Ghana, US-East, US-West, EU-Frankfurt, UK-London, CA-Central). The median substrate-performance signal.",
      "unit": "milliseconds",
      "direction": "lower_is_better",
      "baseline": 450,
      "targets": {
        "q1": 420,
        "q2": 390,
        "q3": 360,
        "q4": 330,
        "year_2": 280
      },
      "thresholds": {
        "green": 360,
        "yellow": 440
      },
      "data_source_kind": "prometheus",
      "owner": "OWN_ENGINEERING",
      "review_cadence_days": 7,
      "linked_pillar_ids": [
        "PILLAR_SUBSTRATE_OWNERSHIP"
      ]
    },
    {
      "id": "METRIC_CALL_SETUP_LATENCY_P95_P99",
      "dimension": "DIM_TECHNICAL",
      "name": "Call setup latency (P95 + P99, by cell)",
      "description": "P95 and P99 call setup latency per cell. Tail-latency evidence — the percentiles enterprise buyers evaluate against contractual SLA.",
      "unit": "milliseconds",
      "direction": "lower_is_better",
      "baseline": 1100,
      "targets": {
        "q1": 950,
        "q2": 850,
        "q3": 750,
        "q4": 650,
        "year_2": 550
      },
      "thresholds": {
        "green": 750,
        "yellow": 1000
      },
      "data_source_kind": "prometheus",
      "owner": "OWN_ENGINEERING",
      "review_cadence_days": 7,
      "linked_pillar_ids": [
        "PILLAR_SUBSTRATE_OWNERSHIP"
      ]
    },
    {
      "id": "METRIC_E2E_CONVERSATIONAL_LATENCY",
      "dimension": "DIM_TECHNICAL",
      "name": "End-to-end conversational latency including barge-in (P95)",
      "description": "P95 time from end-of-user-utterance to start-of-agent-response, including barge-in resumption. The single number that determines whether the voice experience feels human.",
      "unit": "milliseconds",
      "direction": "lower_is_better",
      "baseline": 720,
      "targets": {
        "q1": 650,
        "q2": 580,
        "q3": 520,
        "q4": 470,
        "year_2": 400
      },
      "thresholds": {
        "green": 550,
        "yellow": 720
      },
      "data_source_kind": "prometheus",
      "owner": "OWN_APPLIED_AI",
      "review_cadence_days": 7,
      "linked_pillar_ids": [
        "PILLAR_SUBSTRATE_OWNERSHIP",
        "PILLAR_HYBRID_INTELLIGENCE"
      ]
    },
    {
      "id": "METRIC_SESSION_FAILURE_RATE",
      "dimension": "DIM_TECHNICAL",
      "name": "Session failure rate",
      "description": "Proportion of sessions that terminate in a failure mode (unreachable, transcoding error, agent runtime crash, etc.). Trending downward as platform reliability matures.",
      "unit": "percent",
      "direction": "lower_is_better",
      "baseline": 1.8,
      "targets": {
        "q1": 1.4,
        "q2": 1.1,
        "q3": 0.8,
        "q4": 0.5,
        "year_2": 0.3
      },
      "thresholds": {
        "green": 0.8,
        "yellow": 1.3
      },
      "data_source_kind": "prometheus",
      "owner": "OWN_ENGINEERING",
      "review_cadence_days": 7,
      "linked_pillar_ids": [
        "PILLAR_SUBSTRATE_OWNERSHIP"
      ]
    },
    {
      "id": "METRIC_MODEL_ROUTING_SUCCESS_RATE",
      "dimension": "DIM_TECHNICAL",
      "name": "Model routing success rate",
      "description": "Proportion of model-gateway routing decisions that produce successful inference (completion + within-budget latency + no fallback cascade). Evidence of hybrid-intelligence stack operational quality.",
      "unit": "percent",
      "direction": "higher_is_better",
      "baseline": 96.5,
      "targets": {
        "q1": 97.5,
        "q2": 98.2,
        "q3": 98.8,
        "q4": 99.2,
        "year_2": 99.6
      },
      "thresholds": {
        "green": 98.8,
        "yellow": 97
      },
      "data_source_kind": "prometheus",
      "owner": "OWN_APPLIED_AI",
      "review_cadence_days": 7,
      "linked_pillar_ids": [
        "PILLAR_HYBRID_INTELLIGENCE"
      ]
    },
    {
      "id": "METRIC_INFRA_COST_PER_MINUTE",
      "dimension": "DIM_TECHNICAL",
      "name": "Infrastructure cost per minute",
      "description": "Fully-loaded infrastructure cost per voice-minute served. Trending downward as scale efficiency compounds; primary input into unit-economic leadership.",
      "unit": "usd_per_minute",
      "direction": "lower_is_better",
      "baseline": 0.045,
      "targets": {
        "q1": 0.04,
        "q2": 0.035,
        "q3": 0.03,
        "q4": 0.026,
        "year_2": 0.02
      },
      "thresholds": {
        "green": 0.03,
        "yellow": 0.04
      },
      "data_source_kind": "database",
      "owner": "OWN_ENGINEERING",
      "review_cadence_days": 14,
      "linked_pillar_ids": [
        "PILLAR_UNIT_ECONOMICS",
        "PILLAR_SUBSTRATE_OWNERSHIP"
      ]
    },
    {
      "id": "METRIC_UPTIME_BY_CELL",
      "dimension": "DIM_TECHNICAL",
      "name": "Uptime per cell and jurisdiction (vs SLA)",
      "description": "Rolling 30-day uptime for each operational cell (Ghana, US-East, US-West, EU-Frankfurt, UK-London, CA-Central) measured against the contractual SLA. Evidence of multi-jurisdictional operational reality.",
      "unit": "percent",
      "direction": "higher_is_better",
      "baseline": 99.88,
      "targets": {
        "q1": 99.92,
        "q2": 99.94,
        "q3": 99.96,
        "q4": 99.98,
        "year_2": 99.99
      },
      "thresholds": {
        "green": 99.95,
        "yellow": 99.9
      },
      "data_source_kind": "prometheus",
      "owner": "OWN_ENGINEERING",
      "review_cadence_days": 7,
      "linked_pillar_ids": [
        "PILLAR_SUBSTRATE_OWNERSHIP",
        "PILLAR_MULTI_JURISDICTIONAL"
      ]
    },
    {
      "id": "METRIC_ANALYST_MENTIONS",
      "dimension": "DIM_STRATEGIC",
      "name": "Analyst mentions (Gartner, Forrester, IDC, equivalent)",
      "description": "Cumulative count of named mentions in published research from Gartner, Forrester, IDC, and equivalent tier-one analyst organizations. Leading indicator of category positioning.",
      "unit": "count",
      "direction": "higher_is_better",
      "baseline": 2,
      "targets": {
        "q1": 5,
        "q2": 10,
        "q3": 18,
        "q4": 28,
        "year_2": 50
      },
      "thresholds": {
        "green": 18,
        "yellow": 10
      },
      "data_source_kind": "analyst_feed",
      "owner": "OWN_MARKETING",
      "review_cadence_days": 30,
      "linked_pillar_ids": [
        "PILLAR_CATEGORY_NARRATIVE"
      ],
      "linked_mechanic_ids": [
        "MECH_ANALYST_RECOGNITION"
      ]
    },
    {
      "id": "METRIC_NAMED_CASE_STUDIES",
      "dimension": "DIM_STRATEGIC",
      "name": "Named customer case studies published",
      "description": "Cumulative count of case studies published with named customer attribution. Primary commercial credibility mechanic.",
      "unit": "count",
      "direction": "higher_is_better",
      "baseline": 1,
      "targets": {
        "q1": 3,
        "q2": 7,
        "q3": 12,
        "q4": 18,
        "year_2": 35
      },
      "thresholds": {
        "green": 12,
        "yellow": 6
      },
      "data_source_kind": "manual_entry",
      "owner": "OWN_SOLUTIONS",
      "review_cadence_days": 30,
      "linked_pillar_ids": [
        "PILLAR_CATEGORY_NARRATIVE",
        "PILLAR_COMPLIANCE_DEPTH"
      ],
      "linked_mechanic_ids": [
        "MECH_REFERENCE_ACTIVATION"
      ]
    },
    {
      "id": "METRIC_SOVEREIGN_PIPELINE_REVENUE",
      "dimension": "DIM_STRATEGIC",
      "name": "Sovereign deals in pipeline (revenue signal)",
      "description": "Forward-looking revenue in the pipeline for the Sovereign SKU / sovereign customer segment. The leading-indicator revenue signal for strategic-customer activation.",
      "unit": "usd",
      "direction": "higher_is_better",
      "baseline": 500000,
      "targets": {
        "q1": 1000000,
        "q2": 2500000,
        "q3": 5000000,
        "q4": 10000000,
        "year_2": 25000000
      },
      "thresholds": {
        "green": 5000000,
        "yellow": 2000000
      },
      "data_source_kind": "crm",
      "owner": "OWN_CEO",
      "review_cadence_days": 14,
      "linked_pillar_ids": [
        "PILLAR_MULTI_JURISDICTIONAL",
        "PILLAR_COMPLIANCE_DEPTH"
      ],
      "linked_mechanic_ids": [
        "MECH_COMPLIANCE_UNLOCK",
        "MECH_INTERNATIONAL_EXPANSION"
      ]
    },
    {
      "id": "METRIC_INTERNATIONAL_REVENUE_SHARE",
      "dimension": "DIM_STRATEGIC",
      "name": "Share of revenue outside core (US) market",
      "description": "Proportion of ARR generated in non-US markets. Tracks the §16.5 / §16.7 multi-jurisdictional operational reality pillar's commercial traction.",
      "unit": "percent",
      "direction": "higher_is_better",
      "baseline": 8,
      "targets": {
        "q1": 12,
        "q2": 18,
        "q3": 25,
        "q4": 33,
        "year_2": 45
      },
      "thresholds": {
        "green": 25,
        "yellow": 15
      },
      "data_source_kind": "database",
      "owner": "OWN_CEO",
      "review_cadence_days": 30,
      "linked_pillar_ids": [
        "PILLAR_MULTI_JURISDICTIONAL"
      ],
      "linked_mechanic_ids": [
        "MECH_INTERNATIONAL_EXPANSION"
      ]
    },
    {
      "id": "METRIC_CATEGORY_SEARCH_GROWTH",
      "dimension": "DIM_STRATEGIC",
      "name": "Category search growth (\"sovereign voice AI\" and related)",
      "description": "Google Trends + equivalent search-volume growth rate for category queries (\"sovereign voice AI\", \"GDPR voice AI\", \"HIPAA voice AI\", \"on-device voice AI\"). Leading indicator that the category narrative is gaining external market recognition.",
      "unit": "percent_yoy",
      "direction": "higher_is_better",
      "baseline": 45,
      "targets": {
        "q1": 60,
        "q2": 90,
        "q3": 130,
        "q4": 180,
        "year_2": 250
      },
      "thresholds": {
        "green": 130,
        "yellow": 70
      },
      "data_source_kind": "search_trends_api",
      "owner": "OWN_MARKETING",
      "review_cadence_days": 14,
      "linked_pillar_ids": [
        "PILLAR_CATEGORY_NARRATIVE"
      ],
      "linked_mechanic_ids": [
        "MECH_ANALYST_RECOGNITION",
        "MECH_NEW_LOGO_ACQUISITION"
      ]
    },
    {
      "id": "METRIC_PARTNER_ECOSYSTEM_GROWTH",
      "dimension": "DIM_STRATEGIC",
      "name": "Certified partner ecosystem growth",
      "description": "Cumulative count of certified partners (integration partners, solution partners, resellers). Evidence of ecosystem gravitational pull — the §16.7 Phase 5/6 commitment.",
      "unit": "count",
      "direction": "higher_is_better",
      "baseline": 8,
      "targets": {
        "q1": 18,
        "q2": 35,
        "q3": 60,
        "q4": 100,
        "year_2": 200
      },
      "thresholds": {
        "green": 60,
        "yellow": 30
      },
      "data_source_kind": "database",
      "owner": "OWN_SOLUTIONS",
      "review_cadence_days": 30,
      "linked_pillar_ids": [
        "PILLAR_ECOSYSTEM_BREADTH"
      ],
      "linked_mechanic_ids": [
        "MECH_INTEGRATION_ADOPTION",
        "MECH_DEVELOPER_ECOSYSTEM"
      ]
    }
  ],
  "competitor_reference_set": [
    {
      "id": "COMP_VAPI",
      "cluster": "wrapper_platform",
      "display_name": "Vapi",
      "primary_positioning": "voice AI API wrapper over managed LLM + carrier abstraction"
    },
    {
      "id": "COMP_RETELL",
      "cluster": "wrapper_platform",
      "display_name": "Retell AI",
      "primary_positioning": "conversational voice agent platform for developers"
    },
    {
      "id": "COMP_BLAND",
      "cluster": "wrapper_platform",
      "display_name": "Bland AI",
      "primary_positioning": "phone call automation with custom voice agents"
    },
    {
      "id": "COMP_GOOGLE_CCAI",
      "cluster": "hyperscaler_native",
      "display_name": "Google Contact Center AI",
      "primary_positioning": "Cloud-native omnichannel contact center with integrated conversational AI"
    },
    {
      "id": "COMP_MS_COPILOT_STUDIO",
      "cluster": "hyperscaler_native",
      "display_name": "Microsoft Copilot Studio",
      "primary_positioning": "Microsoft cloud bot + voice builder inside Dynamics / Teams"
    },
    {
      "id": "COMP_GENESYS",
      "cluster": "enterprise_voice",
      "display_name": "Genesys Cloud CX",
      "primary_positioning": "enterprise contact center suite with AI add-ons"
    },
    {
      "id": "COMP_NICE",
      "cluster": "enterprise_voice",
      "display_name": "NICE CXone",
      "primary_positioning": "enterprise CXaaS with Enlighten AI"
    },
    {
      "id": "COMP_FIVE9",
      "cluster": "enterprise_voice",
      "display_name": "Five9",
      "primary_positioning": "cloud contact center with IVA stack"
    }
  ],
  "review_cadences": [
    {
      "id": "CADENCE_SCOREBOARD_WEEKLY",
      "name": "Weekly Scoreboard Review",
      "frequency": "weekly",
      "dimensions_reviewed": [
        "DIM_COMMERCIAL",
        "DIM_PRODUCT",
        "DIM_TECHNICAL"
      ],
      "section16_7_cadence_link": "CADENCE_WEEKLY_OPERATIONAL"
    },
    {
      "id": "CADENCE_SCOREBOARD_MONTHLY",
      "name": "Monthly Scoreboard Review",
      "frequency": "monthly",
      "dimensions_reviewed": [
        "DIM_COMMERCIAL",
        "DIM_PRODUCT",
        "DIM_TECHNICAL",
        "DIM_STRATEGIC"
      ],
      "section16_7_cadence_link": "CADENCE_MONTHLY_STRATEGIC"
    },
    {
      "id": "CADENCE_SCOREBOARD_QUARTERLY",
      "name": "Quarterly Scoreboard Ratification",
      "frequency": "quarterly",
      "dimensions_reviewed": [
        "DIM_COMMERCIAL",
        "DIM_PRODUCT",
        "DIM_TECHNICAL",
        "DIM_STRATEGIC"
      ],
      "section16_7_cadence_link": "CADENCE_QUARTERLY_RATIFICATION"
    },
    {
      "id": "CADENCE_SCOREBOARD_ANNUAL",
      "name": "Annual Scoreboard Trajectory Review",
      "frequency": "annual",
      "dimensions_reviewed": [
        "DIM_COMMERCIAL",
        "DIM_PRODUCT",
        "DIM_TECHNICAL",
        "DIM_STRATEGIC"
      ]
    }
  ],
  "public_apis": {
    "envelope": "https://api.aivaon.com/api/v1/aivaon/scoreboard",
    "dimensions": "https://api.aivaon.com/api/v1/aivaon/scoreboard/dimensions",
    "metrics": "https://api.aivaon.com/api/v1/aivaon/scoreboard/metrics",
    "competitors": "https://api.aivaon.com/api/v1/aivaon/scoreboard/competitors",
    "cadences": "https://api.aivaon.com/api/v1/aivaon/scoreboard/cadences",
    "live_projection": "https://api.aivaon.com/api/v1/aivaon/scoreboard/projection",
    "jsonld": "https://api.aivaon.com/api/v1/aivaon/scoreboard/jsonld",
    "manifest": "https://api.aivaon.com/api/v1/aivaon/scoreboard/manifest.json"
  },
  "public_pages": {
    "doctrine": "https://www.aivaon.com/category-leadership/scoreboard",
    "dimensions": [
      {
        "id": "DIM_COMMERCIAL",
        "url": "https://www.aivaon.com/category-leadership/scoreboard#dim_commercial"
      },
      {
        "id": "DIM_PRODUCT",
        "url": "https://www.aivaon.com/category-leadership/scoreboard#dim_product"
      },
      {
        "id": "DIM_TECHNICAL",
        "url": "https://www.aivaon.com/category-leadership/scoreboard#dim_technical"
      },
      {
        "id": "DIM_STRATEGIC",
        "url": "https://www.aivaon.com/category-leadership/scoreboard#dim_strategic"
      }
    ]
  },
  "a2a_skills": [
    "scoreboard_metric_lookup",
    "scoreboard_dimension_snapshot",
    "scoreboard_trajectory_query",
    "competitor_win_rate_query",
    "category_search_growth_query",
    "category_leadership_index_lookup",
    "competitive_benchmark_lookup",
    "external_report_pack_request"
  ],
  "integrity": {
    "schema_id": "aivaon.section16.8.category_scoreboard.v1",
    "json_schema_path": "backend/artifacts/aivaon-section16.8-category-scoreboard.schema.json",
    "mutation_workflow": "PR to canonical artifact + §16.8 CI gate validation",
    "counts": {
      "measurement_dimensions": 4,
      "metrics": 26,
      "metrics_by_dimension": {
        "DIM_COMMERCIAL": 7,
        "DIM_PRODUCT": 6,
        "DIM_TECHNICAL": 7,
        "DIM_STRATEGIC": 6
      },
      "competitor_reference_set": 8,
      "review_cadences": 4
    }
  },
  "contact": {
    "organization": "AIVAON (WorkSpax LLC)",
    "website": "https://www.aivaon.com",
    "measurement_correspondence": "measurement@aivaon.com",
    "analyst_correspondence": "analyst@aivaon.com",
    "generic_support": "support@aivaon.com"
  }
}