Industries
Domain context changes what good data looks like.
ASEDUCARE combines project guidelines with language and subject context across the industries explicitly represented in its current service portfolio.
Industry workflows
Start with the environment the data must represent.
Terminology, edge cases, access expectations and review roles differ by sector. Select an industry to see the source-backed use cases and relevant services.
AI & ML Research
Human-prepared training data for speech, vision and natural-language systems.
- Speech
- Text
- Images
- Video
Healthcare
Transcription, specialist input and multilingual data support for clinical and medical contexts.
- Clinical audio
- Medical documents
- Specialist text
- Images
Education & E-learning
Voice-over, subtitling, localization and data support for digital learning.
- Lessons
- Recorded classes
- Learning documents
- Voice tracks
E-commerce & Retail
Multilingual product content, copy editing and visual data for global commerce.
- Product copy
- Catalogues
- Product images
- Marketing content
Legal & Compliance
Transcription and translation workflows for legal proceedings and documentation.
- Proceeding audio
- Legal documents
- Case materials
- Compliance content
Gaming & AR/VR
Voice, content and localization support for immersive interactive products.
- Game scripts
- Voice recordings
- Interface strings
- Video
Software & Digital Products
Localization for interfaces, help content, applications and digital customer journeys.
- UI strings
- Help files
- Web copy
- Application content
Media & Entertainment
Timed text, voice, translation and production support for audio-visual content.
- Video
- Audio
- Scripts
- Graphics
Cross-industry foundations
The controls remain consistent, even when the content does not.
Projects can share a delivery structure while preserving the distinct terminology, language and access needs of each domain.
01
Brief and acceptance criteria
02
Representative pilot data
03
Documented edge cases
04
Human review and correction
05
Schema and format validation
06
Agreed delivery batches
Bring us the domain, the data and the definition of done.
Share the data type, languages, volume and timeline. We’ll use those details to shape a practical first conversation.