How Hive works
A simple process for requesting, collecting, reviewing, and preparing real-world training data.
1. Buyer submits a dataset request
AI teams tell us what type of data they need, such as audio, video, images, screen recordings, or custom multimodal data. They share the target language, region, volume, timeline, and the sourcing problem they face today.
2. We scope the collection
We review the request, clarify requirements, and define what contributors need to capture. That includes data type, quality expectations, allowed formats, consent expectations, and review criteria before collection starts.
3. Contributors complete matching tasks
Approved contributors are matched to relevant paid tasks based on their languages, location, devices, and contribution types. They follow task instructions and upload original data they are permitted to provide.
4. Submissions are reviewed
Each submission is checked before approval. Review includes technical quality, relevance to the task, consent requirements, and whether the file contains sensitive information that should not be included.
5. Approved data is prepared for delivery
Approved files can be organized with metadata, review notes, and licensing or consent records so the buyer can evaluate the collection and decide next steps. Delivery timelines depend on the project, not an instant pipeline.
6. Contributors get paid after approval
Contributor payments are based on approved submissions only. Payment workflows will be enabled before paid tasks go live.