In Active Development · Dar es Salaam Pilot Phase
mkato · mobility data infrastructure · africa
Building the data backbone
for how Africa's cities move.
Development Status: Mkato and Dira are both in active development. The Dar es Salaam pilot is underway. The platform is not yet publicly available. If you are an operator, institution, or developer interested in early access, data partnerships, or pilot participation — register your interest below or reach out directly.
Mkato is a mobility data infrastructure system that captures, structures, and distributes
ground-truth transit data across Africa's informal urban networks. Informal transit systems
carry the majority of people across African cities — but they operate entirely outside conventional
data systems. Mkato is building the underlying layer that makes this network legible,
queryable, and operationally useful. Starting in Dar es Salaam. Built for the continent.
Informal transit networks carry the majority of urban passengers across Africa's cities. In Dar es Salaam, daladalas account for over 80% of all motorised trips. These systems are dynamic and demand-driven, shaped in real time by road conditions and operator behaviour rather than fixed routes or scheduled timetables. They work — but they are invisible to every digital platform in existence.
While partial maps and isolated datasets exist, the underlying system remains fragmented, inconsistently updated, and largely disconnected from formal planning and digital infrastructure. No operator has route performance data. No city has a live transit network map. No developer has a reliable data layer to build on. The gap is not technological — it is infrastructural.
Conventional mapping systems capture less than 10% of Dar es Salaam's transit reality. The remaining 90%, where most people actually move, remains structurally invisible — not because it cannot be mapped, but because no one has built the infrastructure to capture it.
City planners, logistics operators, and development institutions make billion-dollar decisions without access to basic transit network data. Infrastructure investment, last-mile delivery, and urban policy are all operating on incomplete information.
African cities lose over $5 billion annually to traffic congestion — in wasted fuel, lost productivity, and supply chain delays. The absence of structured mobility data makes every dollar of that loss structurally impossible to address.
Dira · Mobility Intelligence Layer
03
Internal System · Embedded in Mkato
Dira is Mkato's internal routing and mobility intelligence layer. It is not a separate product. It is the processing engine that converts raw mobility signals captured by the Mkato App into structured, queryable infrastructure that the rest of the system depends on.
Every route geometry, stop record, flow pattern, and coverage layer that Mkato delivers to enterprise clients passes through Dira. It is the intelligence between data collection and data delivery.
Dira is not marketed separately. It is the intelligence layer inside Mkato. Enterprise clients who access mobility data through Mkato are accessing data that Dira has structured, validated, and maintained. The brand distinction exists for technical clarity, not commercial separation.
Dira handles what no off-the-shelf system can: continuous validation of informal transit data that has no fixed schedule, no standardised reporting, and no existing digital reference. Every record Dira produces is net new to the world's data supply.
The intelligence layer is what separates a navigation app from infrastructure. Mkato is infrastructure. Dira is why.
Three wireframe-level diagrams showing how Mkato is structured, where Dira sits inside the system, and how data flows from street-level movement to enterprise intelligence output.
Diagram 01 · Mkato System Architecture
Mkato Technologies
│
Mkato App
Consumer · Data Capture
API Output
Enterprise Delivery
↓
↕
↑
Mobility Dataset · Ground-Truth Layer
Single integrated system. Three functional layers. One unified data backbone.
Diagram 02 · Dira Inside Mkato
Mkato System Boundary
Mkato App · Signal Collection
↓
Dira Intelligence Engine
Validate
Structure
Update
Expose
↓
Enterprise API · Data Delivery
Dira is not a separate product. It is the processing layer inside Mkato.
Diagram 03 · Data Flow · Movement to Intelligence
Urban Movement
Commuters · Operators
→
Mkato App
Signal Capture · Offline
→
Dira Processing
Validate · Structure · Update
→
Mkato Intelligence
Routes · Stops · Flow
→
Operator Action
Planning · Logistics · Policy
Every commuter journey generates data. Dira processes it. Mkato delivers it as infrastructure.
Mkato's mobility data infrastructure serves three institutional segments. Each accesses the same ground-truth dataset — structured differently for the decisions each segment needs to make.
Segment 01 · Government
City Agencies and Urban Authorities
Municipal transport departments, planning ministries, and urban development agencies that require accurate, current transit network data to make evidence-based decisions.
Transit route gap analysis and planning
BRT corridor feasibility and design
Equity access and underserved zone mapping
Infrastructure investment evidence base
Development finance project monitoring
Segment 02 · Operators
Transit Operators and Logistics Platforms
Daladala operator cooperatives, last-mile logistics companies, ride-hailing platforms, and supply chain operators requiring network visibility to reduce cost and improve coverage.
Route optimisation and corridor analysis
Demand forecasting by corridor and time period
Depot placement and fleet allocation
Last-mile delivery network design
SaaS dashboard for operator management
Segment 03 · Developers
Platform Developers and Data Partners
Development institutions, research organisations, insurers, and enterprise platforms building mobility-dependent systems that require a structured transit data layer as their foundation.
REST API access — routes, stops, flow data
GeoJSON and GTFS-compatible data exports
Longitudinal datasets for trend analysis
Risk scoring and accessibility modelling
Research and policy dataset licences
All three segments access the same ground-truth dataset. The difference is delivery format, access tier, and agreement structure. Government clients receive procurement-compatible bulk exports. Operators access SaaS dashboards and route performance tools. Developers access versioned REST API endpoints with full technical documentation.