AI that speaks African.
Standard language models collapse when they meet Pidgin, Sheng, or Swahili code-switching. Njiwa closes that gap with crowdsourced, human-verified audio datasets from across the continent.
Live comparison
Prompt in Nigerian Pidgin, looping demonstration
The data gap
1.4 billion people.
Represented by less
than 2% of AI training data.
The vast majority of AI speech and language models were trained primarily on English, Mandarin, and European languages. African dialects are an afterthought, or absent entirely. Njiwa exists to correct this at the source.
Use Cases
Built for teams who
need the real thing.
Whether you're fine-tuning a frontier model, building a voice product, or running linguistic research, our datasets are verified, labelled, and ready for production.
ASR & Voice Interfaces
Train speech recognition systems that actually understand Pidgin commands, Sheng slang, and code-switched conversation.
LLM Fine-Tuning
Ground your language model in authentic African linguistic context, not English approximations of it.
TTS & Voice Synthesis
Build voice products that sound natural to West African, East African, and Southern African ears.
NLP Research
Access labelled corpora across dialects, annotated for accent region, formality level, and code-switching density.
Human-Verified
Every clip reviewed by a native speaker from the target dialect region, not an automated quality filter.
Rich Metadata
Clips labelled with region, age range, formality level, and code-switching density for precise fine-tuning.
Ready to Integrate
Data delivered as clean JSON + audio bundles via S3-compatible storage or custom API endpoint.
Let's build Africa's
AI infrastructure together.
Request access for early API access, custom dataset requests, and enterprise pricing.