
Our solution tackles a key challenge for telecom operators and infrastructure investors across the SADC region, where decisions about where to deploy connectivity infrastructure are hindered by sparse, outdated, or fragmented data. Traditional approaches rely on costly field surveys and incomplete reports, often leading to inefficient capital allocation and missed opportunities to reach underserved communities. We built an intelligent agent system powered by IBM watsonx Orchestrate that synthesises tower coverage data, settlement locations, and socioeconomic indicators to generate actionable investment insights. It brings together five tools: a readiness index ranking countries by investment potential, a coverage gap analyser detecting settlements beyond tower reach, a deployment cost estimator reflecting local logistics, a multi-country comparison tool, and a settlement prioritisation engine that uses geographic heuristics when demographic data is missing. A key strength of our approach is transparent data handling. Instead of hiding data gaps, the system uses proxy metrics such as settlement clustering, proximity to infrastructure, and strategic location to infer density and feasibility while clearly signalling confidence levels. Accessible via web and WhatsApp, the agent enables field teams to query coverage gaps, compare markets, and estimate deployment costs from anywhere, reducing reliance on specialised GIS staff. The solution supports mobile operators expanding rural coverage, development organisations targeting digital inclusion, and investors assessing SADC opportunities. By lowering the time and cost of analysis while improving decision quality, it accelerates connectivity deployment across Southern Africa and demonstrates the power of agentic AI in complex, data-limited environments.
23 Nov 2025