debt_leverage_profile
0.11x Total Debt / Equity (Conservative)
High
SEC-XBRL
interest_rate_sensitivity
~60% of debt is floating-rate; 200bps rate increase adds ~$8-12M annual interest expense on ~$400-600M debt load, compressing thin margins materially
Inferred
Agent_Inference
geopolitical_supply_exposure
Medium intensity; US-China trade tariffs on metals and components disrupt supply chains.
Medium
GICS-commodity-overlay-v1
supply_chain_dependency
Gulf of Mexico (hurricane/regulatory disruption) and West African offshore corridors (political instability, piracy risk)
Inferred
Agent_Inference
international_expansion_readiness
Nigerian naira, Trinidadian dollar, and Mexican peso devaluation risk significant; USD-denominated contracts partially hedge but local cost inflation erodes margins
Inferred
Agent_Inference
geographic_footprint
Operations in Nigeria, Trinidad, Mexico, and Middle East; naira and peso volatility most material; ~40-50% of revenue exposed to non-USD currency fluctuations
Inferred
Agent_Inference
commodity_exposure_profile
Medium intensity; commodities: Steel, Aluminum, Copper, Crude Oil (fuel), Rare Earth Elements, Plastics/Resins; geopolitical: US-China trade tariffs on metals and components disrupt supply chains.
Medium
GICS-commodity-overlay-v1
vendor_lock_dependency_score
Shipyard and drydock capacity is concentrated among few Gulf Coast/international yards; no single vendor >30% but switching costs are high and lead times are long
Inferred
Agent_Inference
business_model_type_primary
Asset-heavy marine transportation; minimal cloud infrastructure dependency; operations run on vessel management and ERP systems, not hyperscaler-dependent SaaS
Inferred
Agent_Inference
business_model_type_secondary
Vessel charter and offshore support services; cloud termination would disrupt back-office ERP and scheduling but not core revenue-generating vessel operations
Inferred
Agent_Inference
switching_cost_profile
Minimal API coupling risk; legacy marine operations software (SAP/Oracle ERP variants); no material third-party API dependencies in revenue-critical workflows
Inferred
Agent_Inference
howey_test_risk_index
Low Howey risk; revenue model is direct vessel charter and marine services—tangible asset deployment with direct labor, not passive investment returns
Inferred
Agent_Inference
regulatory_burden_tier
Medium
Medium
GICS-regulatory-overlay-v1
data_sovereignty_risk
Low GDPR/CCPA exposure; B2B marine services with minimal consumer PII; crew data across EU/African jurisdictions creates modest compliance overhead
Inferred
Agent_Inference
antitrust_exposure_flag
Low antitrust risk; fragmented offshore marine market with Jones Act competition dynamics; no dominant market share in any single segment exceeding ~10-15%
Inferred
Agent_Inference
regulatory_exposure_profile
Medium burden; regimes: FAA, DOT, OSHA, EPA, ITAR, FTC; Export controls and defense procurement rules create contract concentration risk.
Medium
GICS-regulatory-overlay-v1
revenue_model_type
~70-80% transactional day-rate charters; ~20-30% term contracts (1-3 year); low recurring revenue predictability, highly cyclical with oil & gas capex
Inferred
Agent_Inference
monetization_vector
Day-rate vessel charters billed daily/monthly; spot market and term contract mix; revenue directly tied to vessel utilization rates typically 60-85%
Inferred
Agent_Inference
pricing_architecture
Day-rate pricing set by spot market supply/demand; minimal pricing power in oversupply environments; OSV day rates collapsed 50-70% in prior downturns
Inferred
Agent_Inference
pricing_power_rating
Weak to moderate; commodity-like vessel services with rate transparency; pricing power only emerges during tight supply cycles or specialized vessel scarcity
Inferred
Agent_Inference
target_gross_margin_bracket
20.2% Gross Margin (Moderate (20-40%))
High
SEC-XBRL
churn_vulnerability_index
No free-rider problem; B2B charter contracts require payment; churn risk is contract non-renewal when oil majors cut capex, historically high in downturns
Inferred
Agent_Inference
headcount_cost_structure
Near-linear; vessel crew headcount scales directly with active fleet size; adding vessels requires proportional maritime labor, limiting operating leverage
Inferred
Agent_Inference
marginal_cost_of_growth
High marginal cost; fleet expansion requires vessel acquisition/construction ($20-60M per OSV) plus crew; revenue growth is largely asset-linear not sublinear
Inferred
Agent_Inference
franchise_compliance_risk
Not applicable; SEACOR Marine is not a franchise model—directly operated vessel fleet under unified corporate structure
Inferred
Agent_Inference
customer_acquisition_metric
At 10x scale, customer concentration risk increases; OSV market served by ~50-100 oil majors/contractors globally; CAC remains low but fleet capex dominates unit economics
Inferred
Agent_Inference
network_effect_present
No meaningful network effects; vessel utilization is zero-sum; adding vessels doesn't improve value to existing customers; pure asset utilization business
Inferred
Agent_Inference
asset_efficiency_ratio
Low AI displacement risk near-term; vessel operations require certified maritime crews; AI can optimize routing/maintenance scheduling but cannot replace physical vessel operations
Inferred
Agent_Inference
recession_resistance_tier
Tier 4 (highly cyclical); revenue directly correlated to oil & gas E&P capex; prior downturns saw 40-60% revenue declines; minimal recession resistance
Inferred
Agent_Inference
customer_segment_primary
Offshore oil & gas operators and drilling contractors (majors and independents); top 5 customers likely represent 40-60% of revenue
Inferred
Agent_Inference
customer_segment_secondary
Government/military sealift, wind energy installation support, and subsea construction firms; growing but still minority of revenue (~10-20%)
Inferred
Agent_Inference
characteristic_occupations
["11-0000 Management Occupations", "13-0000 Business and Financial Operations Occupations", "15-0000 Computer and Mathematical Occupations", "17-0000 Architecture and Engineering Occupations", "23-0000 Legal Occupations", "33-0000 Protective Service Occupations", "37-0000 Building and Grounds Cleaning and Maintenance Occupations", "41-0000 Sales and Related Occupations", "43-0000 Office and Administrative Support Occupations", "47-0000 Construction and Extraction Occupations", "49-0000 Installation, Maintenance, and Repair Occupations", "51-0000 Production Occupations", "53-0000 Transportation and Material Moving Occupations"]
High
SOC-2018/GICS-overlay
agent_automatable_labor_share
0.3 (HIL — ~30% of characteristic roles agent-automatable)
Medium
SOC-2018 + agentic-exposure-v1
capital_expenditure_profile
21.4% CapEx / Revenue (High-CapEx Infrastructure)
High
SEC-XBRL
sec_cik
0001690334
High
SEC-EDGAR
ticker
SMHI
High
SEC-EDGAR