Real-time fuel intelligence to slash costs for Ugandan used cars
Ugandan used-car owners face rapidly rising fuel prices and high maintenance costs that strain budgets and make traditional vehicle ownership unsustainable.
FuelFlow lets Ugandan drivers log every litre, see live fuel prices from Kampala stations, and get AI recommendations tailored to local traffic, road conditions, and common used-car inefficiencies. Users save 20-30% on fuel through optimal refueling timing, driving tips, and proactive maintenance alerts that prevent mileage degradation.
Ugandan middle-class drivers and small business owners in urban areas like Kampala who depend on imported used cars
Crowdsourced, hyper-local fuel price data combined with AI models trained specifically on Ugandan used Japanese cars (Toyota, Nissan) under local fuel quality and dusty road conditions.
supportive
Create and manage multiple used cars with imported specs and service history
Quick litre entry with automatic efficiency (km/l) calculation
Crowdsourced prices from stations in Kampala, Jinja, and Entebbe
Personalized weekly tips on driving habits and refueling strategy
Visual monthly and yearly spend breakdowns with forecasts
Mileage-based alerts customized for common Uganda used-car failures
Read and share verified efficiency hacks from other Ugandan owners
WhatsApp and email alerts when fuel drops below target price
PDF reports for tax or business expense claims
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| phone | text | Yes |
| location | text | Yes |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| profile_id | uuid | No |
| make | text | No |
| model | text | No |
| year | int | No |
| current_mileage | int | No |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| vehicle_id | uuid | No |
| litres | int | No |
| price_per_litre | int | No |
| odometer | int | No |
| station | text | Yes |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| station_name | text | No |
| price | int | No |
| location | text | No |
| reported_by | uuid | Yes |
| created_at | timestamp | No |
Relationships:
/api/vehiclesFetch user's vehicles with latest efficiency stats
/api/refuelsLog new fuel purchase and trigger efficiency recalculation
/api/pricesGet latest fuel prices near user location
/api/ai-tipsGenerate personalized fuel saving recommendations
/api/dashboardAggregate cost analytics and forecasts
/api/prices/reportSubmit new station fuel price
30 logs per month
None
Up to 20 vehicles
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 95 | 9% | $239 | $2,868 |
| Month 6 | 720 | 17% | $3,427 | $41,124 |
FuelFlow combines live station prices, smart logging, and AI coaching to help used-car owners in Kampala save up to UGX 180,000 every month.
Post free beta offers in the top 5 Ugandan Facebook groups ('Cars Uganda', 'Kampala Drivers', 'Used Cars Marketplace') targeting owners of Toyota, Nissan, and Honda. Offer 3 months Pro free in exchange for 15-minute feedback calls. Partner with two popular mechanics in Kabalagala and Ntinda who will recommend the app to their regular customers in return for co-branded reports.
Large global community
No Uganda-specific stations or AI for local conditions
Hyper-local data and Uganda-tuned AI
Strong price crowdsourcing
US-centric, no maintenance integration
Combined fuel + maintenance for African used cars
Network effects from crowdsourced fuel price data that becomes more accurate with every Ugandan user, creating a defensible local dataset competitors cannot easily replicate.
Fuel prices in Uganda increased over 45% since 2022 while middle-class salaries stagnated, making every litre count. Smartphone penetration in Kampala now exceeds 70% enabling real-time tools.
Target users may be price sensitive to $28/month
Strong free tier with clear upgrade value and annual discount option
Inaccurate AI recommendations damaging trust
Start with rule-based system, use user feedback loop to fine-tune prompts
Slow initial crowdsourced price data
Seed data from public sources and incentivize first 200 users with free Pro
Success: At least 35% indicate they would pay $20+ monthly
Success: 40% weekly active users and average 18% reported savings
Success: 150 signups in first 14 days with 12% conversion to paid
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