debt_leverage_profile
Net debt ~$30M; Net Debt/EBITDA ~2-3x; 20bp rate rise adds ~$60K annual interest cost on floating facilities
Inferred
Agent_Inference
interest_rate_sensitivity
Predominantly floating-rate ship financing; 20bp increase raises annual debt service ~$60-120K, modest but material on thin margins
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
Strait of Hormuz (Middle East cargo exposure) and Bosphorus/Turkish Straits (Black Sea trade routes)
Inferred
Agent_Inference
international_expansion_readiness
Revenue denominated primarily in USD (standard shipping contracts); sovereign FX devaluation risk is minimal for United Maritime
Inferred
Agent_Inference
geographic_footprint
Operates globally but invoices in USD; exposure to EUR and local port currencies is limited and largely hedged through USD freight contracts
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
Ship management and crewing via single third-party managers (e.g., Unitized Ocean Transport); potential >30% operational cost dependency
Inferred
Agent_Inference
business_model_type_primary
Asset-heavy physical shipping operator; cloud infrastructure termination is operationally irrelevant — no cloud-dependent revenue delivery
Inferred
Agent_Inference
business_model_type_secondary
Back-office and vessel management software may use cloud; disruption would affect administration, not core freight revenue
Inferred
Agent_Inference
switching_cost_profile
Minimal API coupling risk; operations rely on physical vessels, standard maritime software, and broker relationships, not proprietary APIs
Inferred
Agent_Inference
howey_test_risk_index
Low Howey risk; revenue derived from physical freight services, not pooled investment contracts or profit-sharing securities
Inferred
Agent_Inference
regulatory_burden_tier
Medium
Medium
GICS-regulatory-overlay-v1
data_sovereignty_risk
Limited GDPR/CCPA exposure; minimal consumer personal data collected; crew data handling under maritime HR rules poses low regulatory risk
Inferred
Agent_Inference
antitrust_exposure_flag
Low; United Maritime is a small-cap dry bulk/tanker operator with sub-1% market share; no dominant market position warranting antitrust scrutiny
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
~80-90% transactional (voyage charters); ~10-20% recurring (time charters); highly spot-market dependent
Inferred
Agent_Inference
monetization_vector
Per-voyage freight rate billing; time-charter daily hire rates; revenue is transactional and tied to commodity shipping demand cycles
Inferred
Agent_Inference
pricing_architecture
Freight rates set by Baltic Exchange indices; company is a price-taker with no independent pricing power; margin stress-tests unfavorably in rate downturns
Inferred
Agent_Inference
pricing_power_rating
Low; commodity freight market — rates determined by global supply/demand; United Maritime cannot unilaterally raise prices
Inferred
Agent_Inference
target_gross_margin_bracket
Gross margins estimated 20-35%; highly variable with fuel (bunker) costs and charter rate cycles
Inferred
Agent_Inference
churn_vulnerability_index
No free-rider risk; each voyage is a discrete contract; repeat customer dependency is moderate, with brokers intermediating most deals
Inferred
Agent_Inference
headcount_cost_structure
Revenue growth is asset-linear, not headcount-linear; doubling revenue requires more vessels, not proportionally more staff
Inferred
Agent_Inference
marginal_cost_of_growth
Marginal growth cost is capital-intensive (vessel acquisition/leasing); operational leverage exists once fleet is deployed at fixed crew costs
Inferred
Agent_Inference
franchise_compliance_risk
Not applicable; United Maritime is not a franchise business
Inferred
Agent_Inference
customer_acquisition_metric
At 10x scale, freight broker dependency intensifies; CAC low per voyage but fleet capex dominates; unit economics scale with fleet utilization rates
Inferred
Agent_Inference
network_effect_present
No meaningful network effects; shipping is a commoditized service; scale provides modest cost advantages but no demand-side network dynamics
Inferred
Agent_Inference
asset_efficiency_ratio
AI displacement risk is low for core vessel operations; potential AI benefit in route optimization and fuel efficiency, not yet material
Inferred
Agent_Inference
recession_resistance_tier
Low recession resistance; dry bulk and tanker demand highly correlated with global trade volumes and industrial production cycles
Inferred
Agent_Inference
customer_segment_primary
Commodity traders, grain exporters, energy companies chartering vessels for bulk cargo transport
Inferred
Agent_Inference
customer_segment_secondary
Industrial raw material importers (steel, fertilizer, coal); customer concentration risk elevated if top 3 charterers exceed 50% revenue
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
Capex concentrated in vessel acquisition and maintenance; limited reallocation toward future-state tech infrastructure; legacy asset-heavy model persists
Inferred
Agent_Inference
sec_cik
0001912847
High
SEC-EDGAR
ticker
USEA
High
SEC-EDGAR