Vision Marine Technologies Inc.
f3d27fe8f5d94ef6ae8e9a22c35c5f11
PRODUCTION_VERIFIED schema v3.0.0 Inferred last heartbeat: 2026-07-24T17:14:37.391561+00:00

Business Model Classification Tokens

contract_cycle_length
null
Inferred
Pending — BM Dev Shop classification run
enterprise_sales_motion
null
Inferred
Pending — BM Dev Shop classification run
procurement_complexity
null
Inferred
Pending — BM Dev Shop classification run
vendor_lock_coefficient
null
Inferred
Pending — BM Dev Shop classification run
consumer_acquisition_channel
null
Inferred
Pending — BM Dev Shop classification run
brand_loyalty_index
null
Inferred
Pending — BM Dev Shop classification run
impulse_vs_considered_purchase
null
Inferred
Pending — BM Dev Shop classification run
retail_distribution_reach
null
Inferred
Pending — BM Dev Shop classification run

Business Model Archetype Classification

University of St. Gallen — 55 Business Model Navigator (Gassmann et al.)

SG-035 Premium WHO High
Direct: pricing_architecture=Premium pricing tied to EV technology differentiation; vulnerable to price compression as legacy OEMs electrify fleets; cost-plus model with limited volume-scale buffer. Corroborated: target_gross_margin_bracket=Estimated 20–35% gross margin bracket; hardware manufacturing compresses margins; scale and powertrain licensing could push toward upper bound over time (High gross margin bracket (>60%) indicates premium positioni)
SG-023
Licensing
VALUE High
SG-013
Experience Selling
WHAT High
SG-024
Lock-in
WHO High
SG-036
Product to Capability
WHAT High
SG-049
Subscription
VALUE High

Hybrid Combination

Premium (SG-035) WHO provides the core structure, combined with Licensing (SG-023) + Experience Selling (SG-013) + Lock-in (SG-024) to form the complete business model fingerprint.

55 Archetypes Evaluated High: 6 Medium: 14 Registry: schemas/sg55_archetype_registry.yaml

Knowledge Graph — All Sections

debt_leverage_profile
Minimal long-term debt; net-cash position typical for early-stage micro-cap; a 20% rate rise immaterially impacts interest expense given negligible borrowings
Inferred
Agent_Inference
interest_rate_sensitivity
Low direct sensitivity; primary risk is higher cost of any future equity/debt raises and dampened discretionary marine buyer demand at elevated rates
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
1) Taiwan/China semiconductor supply for EV battery management systems; 2) rare-earth magnet sourcing from China for electric motor components
Inferred
Agent_Inference
international_expansion_readiness
Revenues primarily CAD/USD denominated; minor EUR exposure via European boat show sales; sovereign devaluation risk low but CAD/USD cross-rate material
Inferred
Agent_Inference
geographic_footprint
Primarily Canada and USA; nascent European presence; three-currency exposure: CAD, USD, EUR — CAD/USD volatility most operationally significant
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
High dependency on single proprietary electric powertrain supplier relationships; E-Motion technology platform represents non-substitutable core IP input
Inferred
Agent_Inference
business_model_type_primary
Hardware/physical product manufacturer; minimal cloud infrastructure reliance; AWS/GCP termination would affect back-office systems, not core product delivery
Inferred
Agent_Inference
business_model_type_secondary
Direct boat and powertrain sales complemented by dealer distribution; cloud termination risk limited to CRM/ERP disruption, not existential
Inferred
Agent_Inference
switching_cost_profile
Low API coupling risk; no significant third-party API dependencies in revenue-critical operations; hardware-centric model insulates from software API lock-in
Inferred
Agent_Inference
howey_test_risk_index
Low Howey risk; revenue derived from tangible goods sales (electric boats/powertrains); no tokenized assets or profit-sharing instruments in primary model
Inferred
Agent_Inference
regulatory_burden_tier
Medium
Medium
GICS-regulatory-overlay-v1
data_sovereignty_risk
Minimal GDPR/CCPA exposure; limited personal data collection; no SaaS or data-monetization layer; compliance burden is low-to-moderate for dealer/customer records
Inferred
Agent_Inference
antitrust_exposure_flag
Negligible antitrust risk; sub-1% market share in recreational marine; no dominant market position, no exclusionary conduct concerns at current scale
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
~95% transactional (one-time boat and powertrain unit sales); recurring revenue minimal, largely limited to service/parts; no meaningful subscription layer
Inferred
Agent_Inference
monetization_vector
Per-unit hardware sales of electric boats and E-Motion powertrain systems; secondary revenue from aftermarket parts, service, and licensing of powertrain technology
Inferred
Agent_Inference
pricing_architecture
Premium pricing tied to EV technology differentiation; vulnerable to price compression as legacy OEMs electrify fleets; cost-plus model with limited volume-scale buffer
Inferred
Agent_Inference
pricing_power_rating
Moderate-low; premium EV positioning provides short-term pricing power, but commoditization risk rises as Brunswick, Mercury Marine enter electric segment
Inferred
Agent_Inference
target_gross_margin_bracket
Estimated 20–35% gross margin bracket; hardware manufacturing compresses margins; scale and powertrain licensing could push toward upper bound over time
Inferred
Agent_Inference
churn_vulnerability_index
No free-rider leakage; physical product model with one-time purchase; repeat purchase cycle is multi-year; churn risk manifests as dealer attrition not subscription cancellation
Inferred
Agent_Inference
headcount_cost_structure
Revenue growth is largely headcount-linear at current stage; manufacturing scale requires proportional production/engineering staff; limited software-driven leverage
Inferred
Agent_Inference
marginal_cost_of_growth
High marginal cost of growth; doubling revenue requires near-doubling of manufacturing inputs, assembly labor, and dealer support headcount at current scale
Inferred
Agent_Inference
franchise_compliance_risk
Dealer network compliance drift is a moderate risk; independent marine dealers may prioritize legacy ICE inventory over EV units without strong contractual incentives
Inferred
Agent_Inference
customer_acquisition_metric
CAC at 10x scale likely decreases via dealer leverage and brand recognition; LTV remains constrained by infrequent repurchase cycles typical of luxury marine segment
Inferred
Agent_Inference
network_effect_present
No meaningful network effect; electric boat ownership does not create value for other owners; brand community exists but does not compound defensibility
Inferred
Agent_Inference
asset_efficiency_ratio
AI displacement risk low; product design and manufacturing not easily AI-automated at this stage; moderate AI benefit possible in demand forecasting and diagnostics
Inferred
Agent_Inference
recession_resistance_tier
Low recession resistance; recreational electric boats are high-ticket discretionary purchases; demand highly correlated with consumer wealth and credit availability
Inferred
Agent_Inference
customer_segment_primary
Affluent recreational boaters and eco-conscious luxury marina operators in North America; high-income households with $150K+ investable assets
Inferred
Agent_Inference
customer_segment_secondary
Boat rental/fleet operators, marine tourism companies, and government/municipal waterway authorities seeking zero-emission compliance solutions
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 oriented toward future-state: EV powertrain R&D, manufacturing capacity expansion, and technology licensing infrastructure rather than legacy ICE asset maintenance
Inferred
Agent_Inference
sec_cik
0001813783
High
SEC-EDGAR
ticker
VMAR
High
SEC-EDGAR

Business Model Components

Core Space

> *Pending Turn 2 — Business Model Type Agent population.*

Interaction Modes

> *Pending Turn 2 — Business Model Type Agent population.*

Product Matrix

> *Pending Turn 2 — Business Model Type Agent population.*

Historical Evolution Log

Live Operational Signals

Signal DateSignal TypeSummary
Source

Evaluation Gate — Persona Stress Tests

SKILL_BUFFETT_VAL_03PASS2026-07-24no unmet atoms among this persona's authored questions
SKILL_LEGAL_SEC_01PASS2026-07-24no unmet atoms among this persona's authored questions
SKILL_SHORT_BEAR_01PASS2026-07-24no unmet atoms among this persona's authored questions
SKILL_MACRO_STRAT_01PASS2026-07-24no unmet atoms among this persona's authored questions
SKILL_OPS_PARTNER_01PASS2026-07-24no unmet atoms among this persona's authored questions

Live Status

No Live Status block found.