OpenTrain AI

What is OpenTrain AI?

OpenTrain AI is a global freelance marketplace designed for sourcing and managing top-tier data labeling talent for AI and machine learning projects. The platform enables businesses to find, vet, and hire skilled data labelers or outsourcing providers from over 110 countries, all while using their preferred annotation software. With a streamlined workflow, milestone-based payments via secure escrow, and a flat, transparent fee structure, OpenTrain AI helps companies reduce data labeling costs and maintain full control over their projects and data privacy.

Key Features

• Global Talent Pool

  Access a wide network of vetted data labelers and AI trainers across 110+ countries, covering diverse domains and languages.

• Tool-Agnostic Integration

  Hire talent to work directly within your chosen data annotation software, avoiding platform lock-ins and maintaining workflow flexibility.

• Transparent Payments

  Utilize a milestone-based escrow system with a flat 15% fee, ensuring secure, direct payments to labelers and clear cost control.

• Flexible Hiring Options

  Source individual freelancers or full-service labeling providers to match any project scale, complexity, or domain expertise.

• AI-Powered Vetting

  Applicants undergo a live chat interview process powered by GPT-4, helping you efficiently identify the best fit for your needs.

• Data Privacy and Control

  Maintain full control over your data by granting access directly to hired talent within your own tools; OpenTrain AI never handles your data.

Use Cases

• Large-Scale Data Annotation : Companies can quickly assemble teams of expert labelers for high-volume image, text, or audio annotation projects.
• Domain-Specific Labeling : Projects requiring specialized expertise, such as medical, legal, or technical data, can source vetted professionals with relevant backgrounds.
• Flexible Workforce Expansion : AI teams can scale up or down as needed by hiring freelancers or agencies on demand, without long-term commitments.
• Cost-Effective Outsourcing : Reduce labeling costs by bypassing traditional platforms' high markups and paying talent directly through a transparent fee model.
• Tool Use Training for LLMs : Find trainers with specific software expertise to create training data for teaching large language models to use real-world tools.

FAQs