Settlement exception detected
R6,480 expected but not yet matched.
InvestigateRetail Intelligence Infrastructure
Know where the money went.
Know what to buy next.
SWYE connects retail financial, stock, supplier and settlement data to help operators understand what happened, identify what needs attention and make better purchasing, margin and cash-flow decisions.
Built for fuel stations, restaurants, convenience stores, grocery retailers and the suppliers that serve them.
AI-assisted reconciliation · stock intelligence · supplier matching · margin protection
Illustrative SWYE Intelligence View
Retailer Today
Sales vs expected settlement
SalesR184,620
Expected SettlementsR173,480
Settlement GapR11,140
Illustrative settlement completeness
94%
Accounted for against sales
~6% illustrative gap (R11,140). Demo data only.
Sales
R184,620
Expected Settlements
R173,480
Settlement Exceptions
R11,140
Gross Margin
24.8%
Current illustrative margin
Stock Cover
6.4 days
Illustrative 0–14 day reading scale. Not a target.
Supplier Credit Exposure
R82,440
Stock opportunity
2L Cooking Oil is projected to sell through before the next supplier payment date.
Review BuyMargin warning
Committed supplier obligations exceed projected available margin by R14,280.
Review MarginThe retail operating problem
Retailers have data.
They don't always have answers.
A retailer may have a POS system, accounting software, bank statements, supplier invoices, stock reports, fuel systems, card settlements and payroll records.
But those systems often answer different questions.
SWYE is designed to connect those operational signals so management can answer the questions that directly affect cash flow and profitability.
01
What should I buy?
Which stock items can I purchase now and sell within my supplier's credit term?
02
What is actually moving?
Which products are selling fastest — and which are tying up cash?
03
Who should I buy from?
Which supplier offers the best commercial outcome for the specific product required?
04
Did I receive all my money?
Have card, fuel, delivery and other settlements matched the sales that generated them?
05
Are my margins enough?
Are current sales margins sufficient to cover committed supplier payments and operating obligations?
Core platform
SWYE Recon Engine
From transaction data to management action.
The SWYE Recon Engine brings together financial and operational data to identify discrepancies, cash-flow pressure, stock risks and margin leakage. It is being designed to reduce the time between a transaction occurring and management understanding what it means.
01
Input
Capture
- Sales
- Stock
- Supplier invoices
- Settlements
- Payments
- Payroll
- Operational data
02
Control
Reconcile
- Expected vs Actual
03
Intelligence
Detect
- Exceptions
- Shortfalls
- Duplicates
- Timing differences
- Stock risks
- Margin pressure
04
Intelligence
Analyse
- AI-assisted interpretation
05
Outcome
Act
- Recommended next action
SWYE does not stop at showing a variance. It is designed to help explain what the variance means operationally.
Reconciliation use cases
SalesSettlement
Confirm that money collected through payment channels is ultimately received and matched.
StockSales
Connect stock movement to actual sales velocity.
InvoiceGRVPayment
Track the commercial journey from supplier invoice through receipt and eventual payment.
PurchaseCredit Term
Assess whether stock bought on supplier credit is likely to convert back into cash before payment becomes due.
SalesMargin
Measure whether achieved margins are sufficient to cover committed costs.
WorkforceSales
Analyse labour deployment relative to sales activity and operating demand.
Illustrative examples
Turn stock into cash before the supplier needs to be paid.
Retail ordering is not only about what is selling.
It is about matching sales velocity + stock on hand + supplier credit term + expected demand + available cash.
SWYE stock intelligence is designed to help operators classify inventory into:
- Buy
- Buy cautiously
- Hold
- Do not buy
- Overstock risk
- Slow-moving stock
Illustrative recommendation
Buy2L Sunflower Oil
- 7-day sales
- 38 units
- Stock on hand
- 11 units
- Supplier term
- 7 days
- Recommended purchase
- 32 units
Current stock → Expected sales → Recommended replenishment
Current stock11
Expected sales (7-day)38
Recommended purchase32
Reason. Projected sell-through falls within the supplier credit period.
Illustrative recommendation
Do not buyPremium Imported Chocolate
- 30-day sales
- 8 units
- Stock on hand
- 46 units
- Recommendation
- Do not buy
Sales demand vs stock held
Sales demand8
Stock held46
Reason. Current stock exceeds projected demand.
From need to supplier
SWYE Marketplace
Once SWYE identifies what the retailer needs, the marketplace is designed to help source the right solution.
The marketplace connects verified operational demand to relevant suppliers rather than relying only on generic product listings.
01
Retailer Need
02
Verified Requirement
03
Supplier Match
04
Compare
05
Purchase
06
Fulfil
07
Measure Outcome
08
New Operational Signal
Demand originates from a real operating need — not only a search bar.
Measure the return on every business need.
Traditional procurement measures spend. SWYE is being designed to measure whether fulfilling a business need actually improved the business.
Possible Return on Need indicators
- cost reduction
- stock turnaround
- revenue generated
- cash recovered
- margin protected
- supplier savings
- jobs supported
- local procurement impact
Illustrative Return on Need
Demo dataNeed: Purchase fast-moving beverages · Illustrative example
R18,400
deployed
R26,200
sales generated
R7,800
gross margin created
Stock Sold Within Credit Term
91%
Illustrative sell-through within supplier credit term.
Return on Need
Positive
All figures in this example are illustrative.
The SWYE ecosystem
One operating loop. Multiple specialised layers.
SWYE is the central investable technology platform. Marketplace extends the Recon Engine. Curated Crates and SBS are supporting layers for fulfilment and financial control — not separate products competing for attention.
DataIntelligenceNeedMatchFulfilAccountNew Data
Layer 01
SWYE Recon Engine
Understand the business
Identifies operational and financial needs.
Layer 02
SWYE Marketplace
Find the solution
Matches validated demand with relevant suppliers and service providers.
Layer 03
Curated Crates
Fulfil selected demand
Supports fulfilment, distribution and last-mile delivery for applicable products and markets.
Layer 04
SBS
Account and comply
Supports accounting, payroll, tax, compliance, management reporting and financial control.
Transaction data feeds the next decision cycle.
SWYE is the intelligence and matching layer connecting the ecosystem.
Built around high-frequency retail operations.
Fuel Retail
- Fuel
- Forecourt
- Convenience store
- Card settlements
- Wet stock
- Supplier payments
- Workforce
Restaurants & QSR
- Food cost
- Stock usage
- Sales
- Delivery channels
- Labour
- Supplier management
- Margins
Grocery & Convenience
- Fast-moving inventory
- Supplier credit
- Price comparison
- Stock ageing
- Cash conversion
- Ordering
Retail Suppliers
- Verified retailer demand
- Sales opportunities
- Fulfilment
- Customer matching
- Commercial intelligence
High transaction volumes create opportunity.
Margins pay the bills.
TransactionsRevenueMarginCash
Retail businesses generate thousands of operational events. Every sale, purchase, delivery, settlement, stock movement and employee hour contributes to a financial result. SWYE is designed around businesses where small leakages repeated at high volume can materially change profitability.
AI-assisted operations
AI that understands the operating context.
SWYE is being developed to use AI as an interpretation and decision-support layer across reconciled business data. Planned and developing capabilities include:
DataReconciliationContextAI InterpretationManagement Action
Anomaly Detection
Identify unusual transactions, missing settlements and unexpected movements.
Reconciliation Assistance
Help match transactions and supporting records.
Stock Forecasting
Estimate likely stock requirements using recent trading behaviour.
Margin Intelligence
Highlight situations where realised margins may not support upcoming commitments.
Supplier Intelligence
Compare relevant sourcing options for identified demand.
Management Explanations
Translate complex operating data into understandable management actions.
AI supports the decision. The financial and operational records remain the evidence.
Built as scalable retail infrastructure.
Retail Systems
POS · Fuel · Banking · Suppliers · Payroll · Accounting
API / Data Layer
Core
SWYE Recon Engine
Intelligence Services
Dashboard
Marketplace
Alerts
Business Action
- TypeScript
- Next.js
- PostgreSQL
- Hosted authentication
- Vercel
- GitHub
- API-first architecture
- Organisational data isolation
- Multi-tenant SaaS architecture
The architecture is being developed with organisational data separation, secure authentication and scalable integrations as core requirements.
Currently building with real retail workflows in mind.
01
Building
- reconciliation workflows
- retailer dashboards
- stock planning
- supplier matching
- marketplace architecture
- organisational permissions
- product and location structures
02
Validating
- retailer use cases
- ordering logic
- settlement reconciliation
- margin protection
- supplier matching logic
- integration requirements
03
Next
- pilot retailer onboarding
- production integrations
- AI-assisted exception analysis
- supplier network growth
- scalable industry templates
Built from operating experience
The problem came before the software.
Kholiswa Pearl Mqotyana
Founder — SWYE
Kholiswa Mqotyana is a Chartered Business Accountant in Practice with more than a decade of finance, accounting and operational experience. Her experience includes financial management across fuel retail and restaurant operations, stock control, management reporting, tax, payroll, compliance and business advisory.
SWYE grew from repeatedly confronting a simple problem: businesses generate large amounts of information, but management still spends significant time trying to determine what happened, where money went and what action should be taken next. The platform is being built around those practical operating questions.
“The goal is not another dashboard. The goal is to help a retailer know what to do next.”
Built in South Africa. Designed for retail markets everywhere.
South AfricaRepeatable Retail Intelligence ModelMultiple Retail Markets
SWYE begins with the operating realities of South African fuel stations, restaurants, convenience stores and grocery retailers. But the underlying problems are global:
- fragmented operating systems
- settlement complexity
- stock tied up in working capital
- supplier credit pressure
- thin margins
- disconnected procurement
- slow management reporting
The long-term opportunity is to build an intelligence layer that can sit across multiple retail ecosystems and markets.
Better business decisions can create wider economic impact.
SWYE's long-term vision extends beyond financial optimisation. By connecting verified business demand with suppliers and measuring where money circulates, the platform can help make local procurement and economic participation more measurable.
Potential impact indicators
- SMEs supported
- local supplier spend
- jobs associated with fulfilled demand
- supplier opportunities created
- retailer cash preserved
- waste reduced
- stock efficiency improved
These are intended future indicators, not current verified outcomes.
Join the programme
We're building with retailers, not around them.
SWYE is looking for fuel, restaurant, grocery and convenience retail operators interested in helping validate the next generation of operational retail intelligence.
Retailers · Suppliers · Strategic Partners · Technology Partners
Talk to SWYE
Use this form for the pilot programme, a product walkthrough, supplier conversations, technology integrations, or funding discussions.