The operating and financial layer for machine commerce.Enter the docs
This public edition preserves the product and credit architecture while withholding exact store-level financial and financing data.PUBLIC-SAFE EDITION
[ 01 ]
Why VEND exists
Physical machines produce real cash flow. Capital still sees only fragments of the operating picture.
The first wedge
Underwrite the machine together with the cash flow it produces.
VEND turns machine activity, payments and operating history into a standardized record that can support reporting, monitoring, underwriting and financing.
Partner footprint780+ locations
Network users500K+
Monthly partner cycles1M+
Initial verticalLaundromats
Partner-network figures describe CoinUp's network and are not VEND revenue, assets under management or a VEND loan portfolio.
[ 02 ]
What VEND does
One machine. One operating record. One financeable history.
01Machine
02Store
03Operator
04Transaction
05Usage
06Uptime
07Revenue
08Settlement
The machine is not the full collateral story. The machine + verified operating cash flow is.
[ 03 ]
The data layer
Financial statements, plus a higher-frequency view of the asset producing the cash flow.
Machine data does not replace financial statements. It adds operating evidence at the machine, store and settlement level.
01Revenue
02Cycles
03Uptime
04Revenue volatility
05Machine age
06Maintenance
07Payment
08Settlement
Store revenuePRIVATE DATA
Exact store-level revenue is withheld publicly.
Machine utilizationObservable
Cycles, usage density and machine-level activity.
Settlement recordMapped
Payment and settlement visibility around financed assets.
Operator historyPersistent
Asset and operator records compound over time.
The hidden value above is not present in the page source; the public edition uses a non-sensitive placeholder rather than CSS-only concealment.
[ 04 ]
Underwriting engine
Four tests. One maximum financeable amount.
[ 01 ]
Cash flow test
Can stressed operating cash flow repay the facility?
[ 02 ]
Asset test
What equipment value can be recovered?
[ 03 ]
Operator test
Who operates the asset, and how have they performed?
[ 04 ]
Settlement test
Can servicing logic be aligned with actual payment flows?
Underwriting outputMAXIMUM FINANCEABLE AMOUNT
Asset case
CAPEX
Monthly cash flow
Advance rate
Debt service
DSCR
Result
Mature domestic store
PRIVATE DATA
PRIVATE DATA
PRIVATE DATA
PRIVATE DATA
PRIVATE DATA
Strong / qualified case
Mature overseas store
PRIVATE DATA
PRIVATE DATA
PRIVATE DATA
PRIVATE DATA
PRIVATE DATA
Strong / qualified case
Ramp-up market store
PRIVATE DATA
PRIVATE DATA
PRIVATE DATA
PRIVATE DATA
PRIVATE DATA
Seasoning / structure required
Public presentation only. Exact CAPEX, cash flow, pricing, leverage, repayment and DSCR figures are intentionally withheld.
PUBLIC UNDERWRITING SUMMARY
What the redacted numbers mean.
MATURE OPERATING SAMPLES
~2.0x–3.4x DSCR
Across the current mature Korea and Mongolia samples, debt-service coverage remains approximately 2.0x–3.4x under the illustrative case of 20% borrower APR, 70% advance and five-year fully amortizing repayment. In simple terms: the sampled operating cash flow covers modeled monthly debt service with a meaningful cushion.
EARLY RAMP-UP MARKETS
Structure more conservatively.
Early Kazakhstan samples do not yet show the same coverage as the mature cohorts. Those assets may require a lower advance rate, more operating history, reserves or other credit support before they fit the same financing structure. VEND is designed to make that difference visible rather than treat every store as equally financeable.
ILLUSTRATIVE CAPITAL ECONOMICS
A simple public view of the financing logic—not final borrower pricing and not an investment offering.
20%Borrower APR
Illustrative borrower pricing used to test whether asset cash flow can support the capital stack.
→15%Capital provider target
Illustrative target return for lending capital in the current financing discussion.
→5 ptsGross spread
Not VEND net profit. It is the gross amount available before underwriting, servicing, reserves, credit losses and operating costs.
PUBLIC CONTEXT, PRIVATE DETAIL
Individual store revenue, CAPEX and store-level DSCR remain withheld. Detailed operating, underwriting and facility data can be shared with qualified investors and financing partners upon request. All financing terms shown here are illustrative and remain subject to underwriting, legal structure and partner approval.
[ 05 ]
Repayment + monitoring
Connect operating visibility to disciplined servicing.
VEND is designed to standardize payment mapping and financing-linked servicing around assets without forcing a new consumer payment experience.
SERVICING DESIGNSettlement schedule / Repayment ratio / Reserve / Covenants
Pair high-frequency operating visibility with a repayment structure designed around the asset's cash flow.
[ 06 ]
Operating proof
Start with real machine networks—not a synthetic lending dataset.
VEND begins with laundromats because connected machines already produce recurring payments, identifiable service events and measurable operating histories.
Partner footprint780+
CoinUp partner locations
Network users500K+
Partner-network users
Monthly cycles1M+
Partner-network activity
Korea / mature domestic
Operating cohort
Established stores with machine and owner-level operating history.
CAPEX
PRIVATE DATA
Monthly CF
PRIVATE DATA
Asset yield
PRIVATE DATA
Resale value
PRIVATE DATA
Mongolia / mature overseas
Scaled cohort
Overseas operating proof beyond a single pilot location.
CAPEX
PRIVATE DATA
Monthly CF
PRIVATE DATA
Asset yield
PRIVATE DATA
Resale value
PRIVATE DATA
Kazakhstan / ramp-up
Early cohort
Useful for showing how underwriting changes during market ramp-up.
CAPEX
PRIVATE DATA
Monthly CF
PRIVATE DATA
Asset yield
PRIVATE DATA
DSCR
PRIVATE DATA
All store-level financial metrics in this section are permanently withheld from the public build.
[ 07 ]
Asset economics
The underwriting record becomes more valuable as operations compound.
Each financed or monitored asset can add repayment history, maintenance history, utilization and recovery data to the next underwriting decision.
01 / OPERATEMachine activity
Transactions, cycles, uptime and settlement.
02 / UNDERWRITECredit decision
Cash flow, asset, operator and settlement tests.
03 / LEARNPortfolio intelligence
Repayment and operating outcomes improve future decisions.
Operating history becomes credit infrastructure.
[ 08 ]
University infrastructure
Campus deployments create a different but highly measurable machine-credit unit.
Resident population, machine count, contract duration, rent structure, utilization and renewal risk can be monitored as part of the asset record.
Live site historyObserved
A real dormitory deployment provides an operating reference case.
Resident populationPRIVATE DATA
Site-specific population is withheld publicly.
Revenue + contributionPRIVATE DATA
Exact campus economics remain confidential.
Equipment investmentPRIVATE DATA
Exact installation and equipment costs are withheld.
[ 09 ]
Capital absorption
Build financing capacity from multiple real origination pools.
VEND sizes greenfield expansion, replacement demand, university infrastructure, repeat operators and overseas rollout separately rather than relying on a single top-down TAM number.
01Domestic new stores
02Equipment replacement
03University infrastructure
04Existing-operator expansion
05Overseas rollout
PUBLIC SCALE VIEWPROVE → SCALE → EXPAND
FACILITY SIZE, TICKET SIZE AND DEPLOYMENT CAPACITY ARE CONFIDENTIAL IN THE PUBLIC EDITION
PROVEPRIVATE DATA
Validate underwriting, servicing and repayment with qualified assets.
SCALEPRIVATE DATA
Expand across repeat operators and multiple origination pools.
EXPANDPRIVATE DATA
Extend the credit infrastructure across machine categories and markets.
[ 10 ]
Scale + business model
The existing machine network is the origination advantage.
01 / EXISTING NETWORKData + distribution
Operator history, machine history, transaction history and installed footprint.
02 / NEW CAPEXOrigination
New stores, second locations, university installations and equipment replacement.
03 / FINANCINGCredit revenue
Underwriting, origination, servicing and monitoring around qualified deployment.
01Underwriting + data fee
02Origination + servicing
03Monitoring + settlement layer
04Direct asset / SPV option
[ 11 ]
Aligned economics
Financing works when the economics improve for every participant.
VEND is designed so that financing expands productive machine deployment while creating better operating evidence for the next credit decision.
01 / OPERATORGrowth capitalMore capital, faster
Verified machine revenue and operating history can support new-location financing, additional machines and refinancing for qualified operators.
02 / MACHINE PLATFORMCoinUp today
DistributionMore financed stores
Financing reduces upfront capital constraints, supporting more locations, more machine deployment, stronger retention and more transaction volume.
03 / CAPITAL PROVIDERVisibilityMore operating visibility
Machine-level revenue, usage, location performance, transaction activity and cash-flow trends add higher-frequency evidence to underwriting.
04 / VENDLearning loopSmarter underwriting
Each financed and monitored machine adds operating, repayment, maintenance and performance history that can improve future underwriting and capital allocation.
Risk does not disappear. Information asymmetry gets smaller as real operating performance becomes more observable and measurable.
Aligned flywheelCapital → Machines → Revenue → Data → Better Underwriting → More Capital
[ 12 ]
Product roadmap
From dumb machines to financeable assets.
VEND starts by creating a persistent operating and financial record for real-world machines. As the network grows, those records become the foundation for underwriting, financing, asset structuring, and machine capital markets.
01ConnectLive / Building
02IntelligenceNext
03UnderwriteIn Development
04FinancePlanned
05Asset LayerFuture
06NetworkLong Term
[ 01 ]Live / Building
Connect
Bring machines online
Create a persistent digital identity for every machine and connect real-world activity to VEND.
Machine identity
Operator and location mapping
Transaction ingestion
Payment and revenue data
Machine activity records
On-chain verification layer
Outcome
A live network of machines with verifiable operating history.
[ 02 ]Next
Intelligence
Turn activity into financial data
Transform raw machine transactions into standardized performance and cash-flow intelligence.
Revenue history
Utilization and transaction frequency
Machine-level cash-flow profiles
Operator performance
Location performance
Data normalization across machine types
Risk and performance monitoring
Outcome
Every connected machine develops a measurable financial profile.
[ 03 ]In Development
Underwrite
Make machine cash flows underwritable
Use verified operating data to determine how much capital a machine, location, or operator can support.
Machine underwriting engine
Cash-flow based risk scoring
DSCR and repayment capacity
LTV / advance-rate models
Operator credit profiles
Portfolio-level analytics
Default and recovery modeling
Outcome
Machine cash flows become underwritable assets rather than opaque small-business risk.
[ 04 ]Planned
Finance
Connect operators to capital
Give operators access to financing while giving capital providers access to verified machine opportunities.
Financing origination
Machine acquisition financing
Equipment-backed credit
Capital provider marketplace
Automated repayment from machine revenues
Portfolio monitoring
Servicing infrastructure
Outcome
Capital flows toward productive machines based on real operating performance.
[ 05 ]Future
Asset Layer
Turn cash flows into investable assets
Aggregate financed machines and their cash flows into standardized financial products.
Machine pools
Credit portfolios
SPV infrastructure
Machine-backed investment products
Digital ownership records
Programmable cash-flow distribution
Regulated tokenization where appropriate
Outcome
A new asset class built on real machines and real revenues.
[ 06 ]Long Term
Network
Build the financial OS for machine commerce
As more machines, operators, and capital providers join VEND, the network continuously improves.
More machines
More transaction data
Better underwriting
Better financing terms
More capital
More machines
Outcome
VEND becomes the data, underwriting, financing, and ownership infrastructure for machine commerce.
Network effectMore machines → More data → Better underwriting → Better financing → More capital → More machines
[ Q&A ]
The short version.
01Why start with laundromats?+
They already combine connected physical machines, recurring payments, identifiable operating events and repeat operator demand. That makes them a practical first vertical for machine-level operating and credit infrastructure.
02Why is machine data useful?+
It adds higher-frequency evidence around the asset producing the cash flow: usage, uptime, payment, settlement and performance deterioration. It complements rather than replaces traditional financial information.
03What is the collateral?+
The machine matters, but the stronger credit case combines recoverable equipment value with verified operating cash flow, location performance, operator history and servicing aligned with the revenue stream.
04Why are some values hidden?+
The public docs intentionally omit exact store-level revenue, CAPEX, cash flow, pricing, leverage, DSCR, facility sizing and other commercially sensitive partner data. Those values are not embedded behind the visual redaction.
05Where does blockchain fit?+
VEND's core product does not require consumers or operators to use crypto. As the network scales, blockchain infrastructure can provide a shared financial record for machine identity, financing, ownership and settlement across markets and capital providers.
Consumers — Existing payment methods Operators — Existing business workflows Capital — Programmable financial infrastructure
06What is the long-term vision?+
Begin with operating intelligence and machine credit, then extend the same infrastructure toward broader financial coordination for increasingly autonomous physical businesses.