Gloseg Technologies builds AI-powered revenue intelligence systems that help tax authorities close compliance gaps, detect evasion patterns, and optimize collection efficiency. Purpose-built for the complexity of African tax regimes and institutional contexts.
African revenue authorities face a structural challenge: large informal economies, limited taxpayer data, and under-resourced audit functions create persistent tax gaps. Manual processes, disconnected data sources, and reactive enforcement strategies leave billions in legitimate revenue uncollected annually.
Our revenue intelligence approach combines machine learning with deep knowledge of African tax law and institutional constraints. We integrate third-party data sources — customs, banking, land registries, business registries — to build comprehensive taxpayer profiles that enable risk-based, evidence-driven enforcement.
Machine learning models that analyze taxpayer behavior, third-party data, and historical patterns to identify high-risk audit targets with precision.
Continuous risk scoring across the entire taxpayer population, updated in real-time as new data flows in from multiple sources.
Econometric and ML-based models for monthly, quarterly, and annual revenue forecasting with scenario analysis capabilities.
Real-time executive dashboards tracking filing rates, payment compliance, audit outcomes, and collection performance by segment.
Automated ingestion and reconciliation of data from banks, customs, land registries, and business registries for cross-matching.
Structured methodology and tooling for estimating and visualizing tax gaps by sector, taxpayer segment, and tax type.
