TransitFlow is the unified platform that gives Nigerian logistics businesses real-time fleet visibility, AI-optimised routing, and digital payment infrastructure — turning fragmented, high-cost operations into a competitive advantage.
Smart trucks on Nigerian roads · Live GPS tracking · Real-time driver HUD
Traditional fleet management is broken. These are the challenges costing Nigerian businesses billions every year — and why we built TransitFlow.
Inefficient routing and lack of real-time tracking lead to missed deadlines and frustrated customers.
Manual processes and disconnected systems waste valuable time and resources across your fleet.
Without proper monitoring, driver safety and vehicle maintenance become reactive rather than proactive.
Unoptimized routes and idling vehicles burn through fuel budgets and increase carbon footprints.
Difficulty tracking driver performance, compliance, and workload distribution across your fleet.
Lack of visibility into maintenance, insurance claims, and operational expenses erodes profit margins.
From smart tracking to health monitoring, our integrated platform provides everything you need for modern fleet management.
How it works
Monitor your entire fleet with precision GPS tracking, live location updates, and comprehensive trip history.
Leverage machine learning algorithms to calculate the most efficient routes, reducing fuel costs and delivery times.
Gain actionable insights with comprehensive dashboards, custom reports, and predictive maintenance alerts.
Empower drivers with an intuitive mobile app for navigation, task management, and instant communication.
Receive instant alerts for speeding, geofence violations, maintenance needs, and critical events.
Track and reduce your carbon footprint with detailed emissions reporting and eco-driving recommendations.
Built specifically for the Nigerian logistics environment — from Lagos traffic jams to remote inter-state corridors.
One unified dashboard gives fleet managers real-time visibility into every vehicle — location, speed, fuel, driver behaviour, and maintenance alerts — across your entire operation.
Our reinforcement learning engine continuously re-plans routes around Lagos's live traffic, road closures, and delivery windows — cutting average trip distance by up to 18% per run.
The companion app puts turn-by-turn navigation, job updates, and compliance checklists right in drivers' hands — no extra hardware required, works on any Android or iOS device.
TransitFlow's AI engine is the core of the platform — not a bolt-on feature. It continuously learns from every vehicle, route, and delivery to make smarter decisions in real time across Nigeria's complex logistics environment.
GPS, OBD-II, sensors stream live from vehicles
On-device AI filters noise and detects real-time anomalies
Models run on GPU-backed infrastructure for deep inference
Optimised routes, alerts, and maintenance schedules generated
Models retrain on new data to improve with every trip
TransitFlow is architected on AWS and NVIDIA technologies — giving us the compute power, security, and global scale to support fleet operations from a single vehicle to tens of thousands across West Africa.
Amazon Web Services provides the cloud backbone for secure storage, API hosting, AI model inference, real-time alerts, analytics, and user management.
Secure storage for vehicle telemetry data, trip recordings, and dashcam footage at scale
Managed relational database for fleet profiles, driver records, and delivery history
Serverless API execution and containerised microservices for real-time event processing
Global CDN ensuring fast dashboard and mobile app delivery across Nigeria and West Africa
Powering our AI dispatching assistant and natural-language fleet query interface
Real-time monitoring, alerting, and observability across all platform services
Secure device management for thousands of GPS trackers and OBD-II sensors in vehicles
Dynamically scale compute capacity during peak delivery hours and city-wide fleet surges
NVIDIA technologies accelerate our AI model development, optimise inference, and power computer vision and real-time data workloads as the platform scales.
GPU-accelerated route optimisation and ML model training using NVIDIA CUDA parallel computing
Optimising AI model inference for low-latency anomaly detection and real-time driver scoring
Edge AI modules deployed in vehicles for on-device computer vision and offline alerting
Serving multiple AI models simultaneously at scale with consistent throughput and SLA guarantees
Our architecture plan: AWS hosts our backend APIs, stores vehicle data securely, runs AI workflows, manages authentication, serves frontend assets via CloudFront, monitors performance via CloudWatch, and supports ML features through Amazon Bedrock. NVIDIA CUDA and TensorRT accelerate model training and real-time inference. NVIDIA Jetson modules process AI at the vehicle edge, reducing cloud latency for time-critical alerts.
Nigeria's logistics sector is at an inflection point. Rising costs, digital adoption, and e-commerce growth have created an urgent demand for intelligent fleet tools — and no one has built the right platform for this market. Until now.
Nigeria's logistics industry is projected to grow rapidly as e-commerce, FMCG distribution, and cross-border trade accelerate. Yet most fleet operators still rely on manual tracking, WhatsApp, and paper manifests.
Smartphone adoption across Lagos, Abuja, and Port Harcourt has crossed a critical threshold. Drivers, dispatchers, and business owners are ready for app-based tools — the infrastructure finally exists.
Online retail in Nigeria grew significantly post-COVID, creating intense last-mile delivery pressure. Logistics companies are stretched thin without visibility tools, losing customers to delivery failures.
Following subsidy removal, fuel costs now represent 40–60% of operating expenses for many fleet operators. AI-driven route optimisation is no longer a luxury — it is a financial survival tool.
Nigeria's government and regulatory bodies are pushing for digital freight records, fleet compliance systems, and transport sector modernisation — creating a tailwind for tech-first logistics platforms.
No dominant AI-native fleet management platform has captured the Nigerian market. This is the window to establish infrastructure, build trust with operators, and lock in network effects.
Nigeria alone has over 2 million commercial vehicles and a logistics sector worth billions — yet the vast majority of operators have no digital fleet management tools. We are building the category-defining platform for African logistics.
Logistics & Haulage Companies
SME and enterprise freight operators managing inter-state cargo
FMCG Distributors
Consumer goods companies with high-frequency last-mile delivery needs
E-Commerce Fulfilment
Online retailers and 3PL providers serving Nigerian e-commerce growth
Delivery Startups
Tech-forward logistics brands building scalable dispatch operations
Nigeria
Lagos, Abuja, Port Harcourt, Kano
Ghana
Accra, Kumasi
Kenya
Nairobi, Mombasa
Rwanda
Kigali
Pan-African expansion roadmap extends to South Africa, Senegal, and Côte d'Ivoire in Phase 4+
SaaS Subscription
Per-vehicle monthly pricing for SME fleets and enterprise plans for large operators
Enterprise Contracts
Custom-scoped deployments with SLA, API access, and dedicated support
AI Credits
Usage-based pricing for advanced analytics, AI route jobs, and predictive maintenance scans
Data & Insights
Anonymised fleet intelligence reports sold to insurers, fuel companies, and urban planners
We are in active beta development with confirmed pilot partners. The problem is validated, the market is ready, and the build is underway.
MVP Status
In Development
Core fleet tracking platform actively being built — beta access opening Q1 2025
Pilot Partners
3 Confirmed
Logistics companies in Lagos confirmed for closed beta programme
Beta Waitlist
50+ Applications
Fleet operators across Nigeria signed up for early access to the platform
Founder Experience
10+ Years
Combined team experience in Nigerian logistics, AI/ML research, and product development
As a logistics operator in Lagos, we lose hours every week to route confusion and fuel overruns. A platform like TransitFlow would immediately change how we run our operations.
Operations Manager
Mid-size haulage company, Lagos
We've been waiting for an African-built fleet management tool that understands our roads, our costs, and our drivers. This is exactly the kind of solution the market needs.
Fleet Director
FMCG distribution company, Abuja
Currently onboarding pilot users across Lagos and Abuja. Beta access opening soon.
TransitFlow was founded by logistics and AI experts with firsthand experience of Nigeria's transportation challenges — not consultants who read about it.
Logistics professional with 5+ years shaping supply chain operations across West Africa. Previously led fleet operations for a major Lagos-based freight company, managing 200+ vehicles and cross-border distribution networks.
“We built TransitFlow because we lived the problem. Nigerian logistics operators deserve world-class tools built specifically for African roads, traffic, and business realities.”
AI/ML researcher with deep expertise in reinforcement learning, computer vision, and real-world mobility data science. Author of published work on urban traffic pattern prediction in sub-Saharan cities.
“The AI we've built isn't a generic product pasted onto African roads. It was trained on Nigerian traffic data, Nigerian road conditions, and Nigerian logistics patterns. That specificity is our edge.”
TransitFlow is in active beta development. These figures reflect our current traction and validated performance targets from pilot testing with Nigerian logistics operators.
Beta goal: average decrease in operational expenses through AI routing
Logistics companies confirmed for beta programme in Lagos
Businesses on our waitlist across Nigeria
Beta goal: reduction through AI-optimised route planning
A transparent, phased plan — from MVP and beta testing today to GPU-accelerated Pan-African scale by 2026.
Q3 2025
Q4 2025 – Q2 2026
Q2 – Q3 2026
Q4 2026
Q1 2027
Q2 – Q4 2027
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