16/11/2025
Exciting Announcement from Uniplexity AI!
We are honoured to share that our research paper, “Building Multilingual AI Systems for African Businesses: GraphRAG & GNN-Based Fine-Tuning for English–Local Language Mapping”, has been selected for a Main Stage Presentation at the Deep Learning IndabaX Zambia 2025.
Urban Hotel, Lusaka
18–19 November 2025
This recognition is a major milestone for our team and for Zambia’s growing AI ecosystem. We extend our sincere gratitude to the Ubuntu AI Community , the Deep Learning Indaba Zambia Organising Committee, and everyone who has continuously supported our work and mission.
About the Research
African businesses communicate daily using a mix of English and local languages such as Bemba, Nyanja, Tonga, Lozi, and many others.
Yet, most AI systems still struggle to understand these multilingual interactions especially the real-life code-switching that happens in customer service, commerce, and everyday business operations.
Our research introduces an innovative GraphRAG + GNN-powered multilingual AI architecture designed specifically for Africa:
Key Capabilities
✅ Accurate mapping between English, Bemba, and Nyanja
✅ Context-aware meaning interpretation beyond direct translation
✅ Up to 45% reduction in semantic errors
✅ 38% improvement in business query resolution (e.g., customer questions, product search)
✅ Optimized for low-compute hardware, making it accessible for African SMEs
By combining Knowledge Graphs, Graph Neural Networks, and reasoning-tuned LLMs, we built a system that helps African businesses communicate more effectively and automate services across languages.
Why This Work Matters
Africa has more than 2,000 languages, yet mainstream AI is still predominantly built for English-speaking environments.
This work contributes to:
• Inclusive AI that understands African languages
• Local-language NLP for practical business environments
• Affordable, low-resource AI innovation
• Tools SMEs can actually deploy and benefit from
Our mission at Uniplexity AI is simple:
To build AI systems that understand Africa in our own languages, with our own context, and for our own economic growth.
