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0.32x Total Debt / Equity (Conservative)

High sensitivity; ~60% variable-rate debt exposure means 200bps rise adds ~$4-6M annual interest cost on ~$200-300M debt load, compressing thin margins

Medium intensity; US-China trade tariffs on metals and components disrupt supply chains.

Strait of Hormuz (Middle East cargo) and Strait of Malacca (Asia-Pacific routing) are top two chokepoints for Pangaea's dry bulk routes

Significant exposure: Brazilian Real, South African Rand, and Indian Rupee volatility vs USD creates freight rate mismatch risk on non-USD contracts

Revenue concentrated in Brazil, South Africa, India; all three currencies historically volatile vs USD, creating 5-15% annual revenue translation risk

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.

Vessel charter counterparties and bunker fuel suppliers (top 2-3) likely represent >30% of voyage costs; limited substitutability in tight market conditions

Minimal cloud dependency; Pangaea is an asset-light maritime logistics operator; 30-day cloud termination would disrupt ops software but not core vessel chartering

Secondary disruption to route optimization and customer portal systems; vessel operations could revert to manual processes within days, limiting catastrophic risk

Low API coupling risk; Pangaea relies on industry-standard maritime platforms (voyage management, AIS tracking); no proprietary API lock-in identified

Low Howey risk; revenue model is traditional freight transportation service contracts — not investment contracts, no profit-sharing from third-party efforts

Medium

Moderate GDPR/CCPA exposure; handles crew data, client logistics data across EU and California jurisdictions; no evidence of robust DPA framework publicly disclosed

Low; operates in fragmented dry bulk shipping market; no dominant market share position; UNCTAD shipping conference regulations more relevant than antitrust

Medium burden; regimes: FAA, DOT, OSHA, EPA, ITAR, FTC; Export controls and defense procurement rules create contract concentration risk.

Primarily transactional (~85-90% voyage/spot charter revenue); small recurring element via COA (contract of affreightment) arrangements, estimated 10-15% of revenue

Freight rate arbitrage and voyage margin capture; earns spread between chartered-in vessel costs and freight rates charged to commodity shippers

Spot-market linked pricing tied to Baltic Dry Index; minimal pricing power buffer; voyage cost pass-through partially hedged via time-charter coverage

Low; commodity shipping rates are market-determined; Pangaea is a price-taker in most segments with limited ability to sustainably price above market

Voyage gross margins typically 10-20%; net margins thin at 3-7%; TCE (time charter equivalent) earnings are primary margin metric used by management

No meaningful free-rider problem; freight services are transactional with clear invoicing; repeat customer retention driven by service reliability, not platform economics

Revenue growth is largely headcount-sublinear; vessel capacity scales without proportional shore-side headcount increases; crewing costs are variable per vessel

Marginal cost of growth tied to vessel chartering costs, not headcount; doubling revenue requires more vessels/charters but minimal back-office scaling

Not applicable; Pangaea does not operate a franchise model

At 10x scale, CAC likely low (relationship-driven B2B freight sales); LTV improves with COA contracts but spot market dominance limits LTV predictability

Weak network effects; larger fleet/route network improves scheduling optionality for customers but no data or platform network effect present

AI displacement risk low-moderate; route optimization AI could reduce voyage costs 2-5% but cannot replace physical vessel operations or commercial relationships

Moderate-low resilience; dry bulk volumes tied to global commodity demand (coal, grain, bauxite); historically correlated with industrial output cycles

Major commodity traders and mining companies (Glencore, Rio Tinto equivalents); top 5 customers likely represent 30-50% of revenue

Steel mills, power utilities, and agricultural exporters requiring irregular bulk freight; lower contract stability than top-tier commodity traders

["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"]

0.3 (HIL — ~30% of characteristic roles agent-automatable)

Capex model is asset-light (chartered vessels vs owned); owned fleet capex (~10-15 vessels) represents maintenance/drydocking spend; limited strategic reallocation to future infrastructure visible

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PANL