Nine Energy Service Inc.
154308ea-0303-401d-9bf7-945759875bae
PRODUCTION_VERIFIED schema v3.0.0 Inferred last heartbeat: 2026-07-21T05:23:20.727341+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
consumption_unit_definition
null
Inferred
Pending — BM Dev Shop classification run
usage_billing_granularity
null
Inferred
Pending — BM Dev Shop classification run
overage_penalty_structure
null
Inferred
Pending — BM Dev Shop classification run
minimum_commitment_floor
null
Inferred
Pending — BM Dev Shop classification run
metered_margin_profile
null
Inferred
Pending — BM Dev Shop classification run
bundle_discount_depth
null
Inferred
Pending — BM Dev Shop classification run
cross_sell_attach_rate
null
Inferred
Pending — BM Dev Shop classification run
bundle_churn_vs_single_churn
null
Inferred
Pending — BM Dev Shop classification run
bundle_margin_blended
null
Inferred
Pending — BM Dev Shop classification run
upsell_pathway_architecture
null
Inferred
Pending — BM Dev Shop classification run

Business Model Archetype Classification

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

SG-049 Subscription VALUE High
Direct: monetization_vector contains [Per-well or per-stage service fee model; revenue directly tied to E&P operator drilling activity and completion intensity; no platform or recurring monetization]; revenue_model_type=~95% transactional (job-by-job completion services); <5% recurring via master service agreements; highly cyclical and volume-dependent with no meaningful subscription revenue
SG-036
Product to Capability
WHAT High

Hybrid Combination

Subscription (SG-049) VALUE provides the core structure, combined with Product to Capability (SG-036) to form the complete business model fingerprint.

55 Archetypes Evaluated High: 2 Medium: 16 Registry: schemas/sg55_archetype_registry.yaml

Knowledge Graph — All Sections

debt_leverage_profile
-3.04x Total Debt / Equity (Negative equity)
High
SEC-XBRL
interest_rate_sensitivity
High sensitivity; ~$400M debt at variable/fixed rates, 200bps rise adds ~$8M annual interest expense, compressing already thin EBITDA margins near breakeven
Inferred
Agent_Inference
geopolitical_supply_exposure
High intensity; OPEC+ supply decisions and Russia-Ukraine conflict drive price volatility.
Medium
GICS-commodity-overlay-v1
supply_chain_dependency
Permian Basin/Gulf Coast oilfield equipment logistics and specialty chemical inputs sourced via Gulf of Mexico corridor; Middle East conflict affecting proppant supply chains
Inferred
Agent_Inference
international_expansion_readiness
Limited international exposure; primary revenues ~90% US-based; minor Canada/Latin America operations face CAD and MXN devaluation risk of moderate concern
Inferred
Agent_Inference
geographic_footprint
~90% US revenue (Permian, Eagle Ford, Haynesville); Canada and Latin America represent <10%; CAD and MXN fluctuation poses limited but real currency translation risk
Inferred
Agent_Inference
commodity_exposure_profile
High intensity; commodities: Crude Oil, Natural Gas, Coal, Refined Petroleum Products, Uranium, Steel (equipment); geopolitical: OPEC+ supply decisions and Russia-Ukraine conflict drive price volatility.
Medium
GICS-commodity-overlay-v1
vendor_lock_dependency_score
Specialty cementing tools and completion equipment from select manufacturers (e.g., specific plug/perf vendors) create moderate lock-in; no single vendor likely exceeds 30% but substitution is operationally disruptive
Inferred
Agent_Inference
business_model_type_primary
Minimal cloud infrastructure dependency; field-service operations rely on proprietary hardware and local software; AWS/GCP/Azure termination would disrupt back-office but not core revenue generation
Inferred
Agent_Inference
business_model_type_secondary
Secondary ERP and scheduling systems likely cloud-hosted; 30-day termination creates ~2-4 week operational disruption; migration feasible within 60-90 days with moderate cost
Inferred
Agent_Inference
switching_cost_profile
Low API coupling risk; operations are hardware/field-service based; minimal third-party API dependencies in revenue-critical workflows; switching cost risk is low
Inferred
Agent_Inference
howey_test_risk_index
Revenue model is fee-for-service oilfield completion services; fails Howey Test on 'expectation of profits from others' efforts'; no securities classification risk applicable
Inferred
Agent_Inference
regulatory_burden_tier
High
Medium
GICS-regulatory-overlay-v1
data_sovereignty_risk
Minimal GDPR/CCPA exposure; customer data is primarily B2B operational/technical data for E&P companies; no consumer PII at scale; compliance burden is low
Inferred
Agent_Inference
antitrust_exposure_flag
Low antitrust risk; Nine Energy holds <5% US completion services market share; fragmented industry with Halliburton, SLB, Baker Hughes dominating; no pricing power concern
Inferred
Agent_Inference
regulatory_exposure_profile
High burden; regimes: EPA, FERC, DOE, CFTC, OSHA, SEC; Accelerating emissions mandates and methane rules threaten capex economics.
Medium
GICS-regulatory-overlay-v1
revenue_model_type
~95% transactional (job-by-job completion services); <5% recurring via master service agreements; highly cyclical and volume-dependent with no meaningful subscription revenue
Inferred
Agent_Inference
monetization_vector
Per-well or per-stage service fee model; revenue directly tied to E&P operator drilling activity and completion intensity; no platform or recurring monetization
Inferred
Agent_Inference
pricing_architecture
Cost-plus pricing with market-rate benchmarking; under E&P budget pressure, Nine cannot hold price; 10-15% price concession risk in downturn without volume offset causes rapid margin deterioration
Inferred
Agent_Inference
pricing_power_rating
Weak pricing power (2/10); commodity-like completion services, customer price sensitivity is high, and larger competitors can subsidize pricing to win contracts
Inferred
Agent_Inference
target_gross_margin_bracket
1.5% Gross Margin (Thin (<20%))
High
SEC-XBRL
churn_vulnerability_index
No free-rider problem; services are discrete contracted jobs; churn risk is high as E&P operators freely switch completion service providers based on price and availability
Inferred
Agent_Inference
headcount_cost_structure
Revenue growth is highly headcount-linear; field crews, engineers, and equipment operators scale 1:1 with job volume; doubling revenue requires near-doubling of field workforce
Inferred
Agent_Inference
marginal_cost_of_growth
Marginal cost of growth is high; each incremental revenue dollar requires proportional labor, equipment, and consumable spend; no software-like operating leverage exists
Inferred
Agent_Inference
franchise_compliance_risk
Not a franchise model; not applicable
Inferred
Agent_Inference
customer_acquisition_metric
At 10x scale, CAC would rise significantly as Nine competes for E&P contracts against larger incumbents; current unit economics marginally positive with EBITDA margins ~5-10% at best
Inferred
Agent_Inference
network_effect_present
No network effects present; completion services are physical, location-specific, and non-cumulative; additional customers do not improve service value for existing customers
Inferred
Agent_Inference
asset_efficiency_ratio
-15.2% Return on Assets (Negative equity)
High
SEC-XBRL
recession_resistance_tier
Tier 4 (highly cyclical); oil price below ~$55/bbl triggers E&P capex cuts and immediate completion services demand destruction; 2020 revenue fell ~50% YoY
Inferred
Agent_Inference
customer_segment_primary
E&P operators (independents and majors) in US unconventional shale basins; customer concentration risk elevated with top 10 customers likely representing 60-70% of revenue
Inferred
Agent_Inference
customer_segment_secondary
Mid-size independent E&P companies in Permian and Haynesville; loss of 2-3 top customers could reduce revenue by 20-30%, representing material concentration risk
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", "19-0000 Life, Physical, and Social Science Occupations", "23-0000 Legal 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", "53-0000 Transportation and Material Moving Occupations"]
High
SOC-2018/GICS-overlay
agent_automatable_labor_share
0.33 (HIL — ~33% of characteristic roles agent-automatable)
Medium
SOC-2018 + agentic-exposure-v1
capital_expenditure_profile
2.8% CapEx / Revenue (Low-CapEx Asset-Light)
High
SEC-XBRL
sec_cik
0001532286
High
SEC-EDGAR
ticker
NINE
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_03PASS2026-07-21no unmet atoms among this persona's authored questions
SKILL_LEGAL_SEC_01PASS2026-07-21no unmet atoms among this persona's authored questions
SKILL_SHORT_BEAR_01PASS2026-07-21no unmet atoms among this persona's authored questions
SKILL_MACRO_STRAT_01PASS2026-07-21no unmet atoms among this persona's authored questions
SKILL_OPS_PARTNER_01PASS2026-07-21no unmet atoms among this persona's authored questions

Live Status

No Live Status block found.