RAG-grounded. Factual. Trusted.
Built on a specialized Retrieval-Augmented Generation pipeline that eliminates hallucinations and provides sourced, accurate answers about Nigeria.
How RAG Works
Retrieve
When you ask a question, QAi searches through 1.2M+ curated knowledge chunks to find the most relevant Nigerian information.
Augment
The retrieved knowledge is combined with your question to give the AI model full context before generating a response.
Generate
The model produces a response grounded in real, verified information — not hallucinated facts or generic knowledge.
Why RAG matters
Standard AI models generate responses from patterns learned during training. This means they often "hallucinate" — confidently stating incorrect information as fact.
QAi's RAG pipeline solves this by grounding every response in verified, curated knowledge about Nigeria. When QAi tells you about the Benin Bronzes, it's drawing from real historical sources, not guessing.
This makes QAi uniquely trustworthy for enterprise use cases where accuracy isn't optional — from financial services to education.
Hallucination-free
Responses grounded in verified Nigerian knowledge
Source-backed
Every answer traceable to curated data sources
Real-time retrieval
Knowledge base continuously updated and expanded
Context-aware
Understands cultural nuances and local terminology
The BIGLLM Architecture
7B Parameters
Optimized for speed and accuracy
Nigerian Corpus
850K+ articles from Nigerian sources
QLoRA Fine-tuning
Efficient adaptation to local data
Multi-source RAG
Parallel knowledge retrieval
Experience the difference.
See how RAG-grounded AI delivers answers you can actually trust.
Try QAi Free