Tryhuman provides a managed marketplace of vetted human annotators for image, text, audio, and video labeling, offering an end‑to‑end workflow that includes task design, quality assurance, and secure data handling. The platform integrates via API/SDK into existing machine‑learning pipelines and supplies real‑time analytics on progress, cost, and accuracy, enabling AI teams to obtain high‑quality training data at scale while reducing turnaround time and expense.
Funding
Funding not disclosed
Founders
Product
Problem
Businesses need a reliable way to collect, verify, and manage human-generated data for training AI models, but existing solutions are often fragmented, costly, and lack scalability.
Solution
Tryhuman offers a platform that connects companies with a vetted network of contributors who perform data annotation, labeling, and validation tasks. The service provides an end‑to‑end workflow that includes task design, quality control, and secure data handling, enabling organizations to obtain high‑quality training data at scale. By automating contributor onboarding and using performance‑based incentives, Tryhuman reduces turnaround time and cost while maintaining consistent data accuracy. Clients can monitor progress and results through a web dashboard that integrates with common machine‑learning pipelines.
Target Audience
Primary customers are AI and machine‑learning teams in technology firms, enterprises, and research institutions that require large volumes of accurately labeled data.
Features
- Managed marketplace of pre‑screened human annotators for image, text, audio, and video labeling
- Built‑in quality assurance tools, including consensus checks and reviewer audits
- API and SDK integrations for seamless task submission from existing ML workflows
- Real‑time analytics dashboard with progress tracking, cost monitoring, and quality metrics
- Secure data transfer and storage compliant with industry privacy standards