Examples by field
AfriAnnotate started with African-language NLP and goes deepest there, but the engine is a general labeling platform — text, speech, images, video, time series and geospatial data. Whatever field you work in, there's a starting point below. These are wayfinders, not tutorials: each links to a recipe or the template gallery.
Language & speech
The flagship: translation, transcription, span labeling and a full speech-corpus pipeline.
- Translation — source text in, translations out.
- Audio transcription — play a clip, type what was said.
- Speech-recording corpus — prompts in, QC'd recordings out.
- Span labeling / NER — entities in text, African-script presets.
- Text templates — classification, sentiment, QA, summarisation.
Climate & land use
Label satellite and drone imagery, or work with sensor readings over time.
- Image templates — bounding boxes, polygon and brush segmentation for land-cover mapping.
- Time-series templates — annotate weather-station, rainfall or air-quality signals.
- Import from cloud storage — pull large image sets from S3 / GCS / Azure.
Health
Triage documents and images with consent tooling built in.
- OCR & multi-page documents — transcribe scanned forms and clinical records.
- Text classification — code case notes or symptom reports.
- Consent & policy — signature-enforced consent and exportable records for sensitive data.
Agriculture
Crop and pest identification from photos, and sensor time series from the field.
- Image classification & bounding boxes — identify crops, disease or pests in field photos.
- Time-series templates — soil-moisture, temperature and yield-sensor streams.
- Work offline — collect and label in the field, sync when you're back online.
Not sure which template fits? The full template gallery groups every built-in config by data type, and the Recipes give click-by-click setups for the most common goals.