Collect, label, and validate machine learning datasets with a vetted African workforce. From Swahili speech to translation and expert review, AfriEval gives AI teams the people and the tooling to produce high quality training data.
The next generation of AI needs data that reflects the world it serves. Africa brings the linguistic diversity, local expertise and contributors to make that possible.
Work with native speakers of Swahili, Yoruba, Amharic, Hausa, Zulu and other African languages.
Contributors are verified and certified for the task types and languages they work in, with senior contributors reviewing their work.
Role-based access, and a record of every submission and review decision against the task it belongs to.
One platform manages the full lifecycle from raw data to export ready training sets.
Bring your own raw data or have contributors record it, and route work to people matched by language and field.
Label, transcribe, tag or rank using templates you can adapt to your model objective.
Consensus and senior review check every judgment before it reaches your training pipeline.
Download structured datasets as Excel, JSON or JSONL, with raw audio and full provenance.
Flexible task types that adapt to your model, data format, and quality requirements.
Image classification, tagging and document or OCR checks, with local context a generic workforce misses.
Named entity recognition, sentiment, intent and translation review in English, Swahili and other African languages.
Transcription and accent-rich speech collection for voice interfaces and ASR models.
Preference ranking, safety review and hallucination checks on model answers.
Review layers keep your datasets accurate, consistent, and traceable.
Several matched contributors answer each task independently, never the same person twice.
Instructions and examples written for your project are shown to contributors as they work.
Senior contributors review work and approve, correct or reject it.
Africa is home to thousands of languages and a multilingual workforce with deep cultural context. That makes it the right place to build representative AI training data, especially for speech, translation and local domain tasks.
We support transcription, translation review, entity tagging, text and image classification, OCR checks, model answer ranking, safety review and custom forms. Languages include Swahili, Yoruba, Amharic, Hausa, Zulu and others. Tell us yours if it is not listed.
Quality is built into the workflow: several contributors answer each task, and senior review approves the result. You can follow progress and review status on every project as work comes in.
We use role-based access, and contributors appear in your data only as pseudonymous codes. Submissions and review decisions are recorded from ingestion to export. Ask us about data handling terms for your project.
Tell us the languages, the kind of data and the format you need, and we will show you how AfriEval can power your models.