OpenTrain AI

OpenTrain AI is a global freelance marketplace that connects existing annotation tools with vetted human data experts worldwide. It enables users to directly hire specialized human data experts for any AI training need, reducing costs, maintaining control, and quickly building high-quality AI training data. The platform supports integration with any data labeling software and offers secure global payments. Additionally, OpenTrain AI provides a fully-managed service where in-house experts handle end-to-end AI data labeling projects.

## How to Use

To use OpenTrain AI, users can create an account and post their data annotation project, optionally anonymously. They will then receive proposals and bids from vetted freelance AI trainers and outsourced labeling providers. After reviewing proposals, users can select and hire labelers, inviting them to join their account on any preferred data labeling software. Projects are funded in milestones via credit card, with funds held in escrow until approval. Alternatively, users can opt for the fully-managed service by requesting a quote, where OpenTrain AI's in-house experts manage the entire project.

OpenTrain AI's

## Key Features

- Global freelance marketplace for AI training data experts (40,000+ vetted trainers) - Compatibility and integration with any data labeling software/tool - Secure global payment system with escrow milestones - Direct hiring and management of freelance human data experts - One-stop sourcing for individual freelancers and outsourced labeling providers - Fully-managed AI data labeling service option - Access to domain-expert AI Trainers for various data annotation needs

## Use Cases

- RLHF (Reinforcement Learning from Human Feedback) - Coding data labeling - STEM Labeling - Reasoning & Planning data annotation - Dataset Curation - Video annotation - Fine-Tuning data preparation - LLMs & Generative AI data - Medical data labeling - Robotics data labeling - 3D Point Cloud annotation - Image annotation - Time Series data labeling - Geospatial data labeling