AI-Driven Operations for a Pan-African Rural Energy Provider
How we built an end-to-end AI platform that unified data from 180+ solar mini-grids, automated site selection, predicted equipment failures, and powered data-driven growth across sub-Saharan Africa.
180+
Mini-grids managed
30K+
Connections served
99%+
Uptime maintained
900t
CO₂ avoided / year
Scaling Clean Energy Across a Continent
Our client operates solar-powered mini-grids that deliver 24/7 electricity to off-grid communities across Madagascar and Mali, with expansion plans into Nigeria and the DRC. Each site serves 300–400 households and small businesses through prepaid, mobile-money energy coupons and smart meters ranging from 100 W to 16 kW.
As the portfolio grew past 180 sites, the existing toolset could no longer keep pace. Critical decisions — where to build next, how to prevent outages, which tariffs to offer — were being made with fragmented data and manual analysis.
No Unified Visibility
Demand, losses, and outage data were scattered across tools with no real-time, cross-portfolio view.
Manual Site Selection
Satellite and survey data for new village identification was analysed manually — slow and inconsistent.
Demand Forecasting Gaps
Limited ability to forecast energy demand growth or size solar plants efficiently for future load.
Fragmented Customer Tools
Sales, prepaid recharges, and local engagement ran on disconnected systems with no shared intelligence.
An End-to-End AI Operating Platform
Working with the client's operations, engineering, and impact teams, we designed and delivered a five-layer AI solution stack — from a unified data foundation through to demand-stimulation models for community impact.
Unified Cloud Data Platform
Consolidated data from smart meters, solar inverters, mobile money platforms, CRM systems, and field surveys into a single cloud warehouse. Standardised historical data from 180+ sites and 30,000+ connections to enable consistent cross-country performance metrics.
Data EngineeringAI-Powered Site Identification
Deployed ML models on satellite imagery and geospatial layers — population density, road access, proximity to existing grids — to score village suitability and project demand. Integrated 20,000 previously analysed sites so models could learn from past decisions and outcomes.
Machine LearningPredictive Operations & Asset Optimisation
Built anomaly detection on production and consumption curves to flag irregular losses, potential meter tampering, or early equipment failure. Developed load-forecasting models using weather data, historical usage, and seasonality to right-size new solar plants and plan upgrades.
AI AutomationCustomer Segmentation & Tariff Optimisation
Segmented customers by consumption profiles, load size, and payment history — distinguishing households, small shops, and productive users like mills and cold rooms. Simulated tariff and coupon structures to balance revenue stability with energy affordability.
Advanced AnalyticsAI-Supported Demand Stimulation
Built scoring models to identify entrepreneurs most likely to benefit from appliance financing and business support. Linked operational data with impact indicators — new businesses, women entrepreneurs, job creation, CO₂ avoided — to quantify the socio-economic value of each village.
Impact AnalyticsFrom Discovery to Scale in Four Phases
Phase 1 — Discovery & Alignment
Deep-dive workshops with operations, data, and impact teams covering mini-grid design, 20-year village licences, and local sales processes. Mapped every digital tool in use.
Phase 2 — Data Foundation & Quick Wins
Rapid consolidation of high-value sources (smart meters, mobile payments) to deliver early dashboards on site performance, losses, and payment behaviour. Anomaly alerts rolled out within weeks.
Phase 3 — Model Development & Pilot
Piloted AI models in a representative subset of villages in Madagascar and Mali, covering different load profiles and socio-economic contexts. Co-designed operational playbooks.
Phase 4 — Scale-Up & Continuous Improvement
Progressive deployment across 180+ sites with live financial and impact KPIs. Continuous model retraining as the client expanded to new villages and markets.
Measurable Outcomes at Scale
Operational & Financial Performance
99%+ availability sustained across all mini-grids despite growing portfolio size, supported by AI-driven monitoring
Scalable model proven 180+ electrified villages and over one million people benefiting from access to electricity
Faster, smarter expansion site-scoring models helped prioritise village roll-out and focus capital on highest-impact locations
Customer & Community Outcomes
30,000+ direct connections and hundreds of thousands of indirect beneficiaries with access to clean electricity
5,200+ businesses connected including 1,500+ women entrepreneurs supported through productive-use programmes
~900 tonnes CO₂ avoided annually by replacing diesel alternatives with renewable mini-grids
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