Collect, label, and validate machine learning datasets with a vetted African workforce. From Swahili speech to medical image segmentation, AfriEval gives enterprise AI teams the infrastructure to produce high quality training data at scale.
The next generation of AI needs data that reflects the world it serves. Africa delivers the linguistic diversity, local expertise, and scalable workforce to make that possible.
Access native speakers of Swahili, Yoruba, Amharic, Hausa, Zulu, and hundreds of regional languages.
A growing pool of vetted, certified contributors and senior contributors across East, West, and Southern Africa.
KYC verified identities, audit trails, role based access, and data handling agreements on every project.
One platform manages the full lifecycle from raw data to export ready training sets.
Ingest raw images, text, audio, or video and route them to contributors matched by language, skill, and domain.
Label, transcribe, tag, segment, or rank using configurable workflows built for your model objective.
Consensus, gold tasks, and senior QA verify every judgment before it reaches your training pipeline.
Receive structured datasets via API, webhook, or connector with full lineage and quality metadata.
Flexible task types that adapt to your model, data format, and quality requirements.
Bounding boxes, segmentation, classification, and object tracking for autonomous, agriculture, and medical imaging.
Named entity recognition, sentiment, intent, and document extraction in English, Swahili, and low resource African languages.
Transcription, speaker identification, and accent rich speech collection for voice interfaces and ASR models.
RLHF, preference ranking, red teaming, safety review, and hallucination detection for frontier models.
Enterprise grade review layers keep your datasets accurate, consistent, and auditable.
Every task is reviewed by matched contributors until agreement meets your threshold.
Known answer tasks continuously measure contributor accuracy and surface drift.
Domain specialists adjudicate disputes and sign off on high stakes outputs.
Kenya and the broader African continent offer a young, multilingual workforce with deep cultural context. That combination is ideal for building representative AI training data, especially for speech, translation, and local domain tasks.
We support image classification, bounding boxes, segmentation, OCR, transcription, translation review, LLM ranking, safety review, and custom forms. Languages include Swahili, Yoruba, Amharic, Hausa, Zulu, and many others.
Quality is built into the workflow: consensus, gold tasks, senior QA, and continuous analytics. Each project tracks agreement, accuracy, and throughput so you can adjust in real time.
Yes. We use role based access, audit logs, KYC verification, and signed data handling terms. All project activity is traceable from ingestion to export.
Talk to our team about data annotation services in Kenya and Africa, and see how AfriEval can power your models.