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Research participant marketplace that gives AI teams and academics fast access to verified, screened human data and feedback.
Outlier is a platform where experts earn freelance income training and evaluating AI by writing prompts, rubrics and rating answers.
Marketplace connecting paid domain-expert contractors to AI labs for data labeling, RLHF and model evaluation work.
Data lab providing expert human data, RL environments, and contextual evaluations to train and assess AI models and agents.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦300,000+ verified, screened participants
- ✦300+ audience targeting filters
- ✦Representative and quota-based sampling
- ✦API and no-code survey tool integrations
- ✦AI-powered participant quality monitoring (Protocol)
- ✦Managed services with dedicated project teams
- ✦Access to vetted domain experts
- ✦Remote AI-training gig work
- ✦Tasks: prompt writing, rubrics, rating answers
- ✦Flexible hours, work from anywhere
- ✦Weekly, quality-based pay
- ✦Roles across coding, STEM and languages
- ✦Free access to paid AI models
- ✦Data annotation and multi-format labeling
- ✦RLHF and human preference feedback
- ✦AI model red-teaming and safety testing
- ✦On-demand vetted ML/prompt engineering talent
- ✦Synthetic data generation
- ✦Structured model evaluation and benchmarking
- ✦Realm: RL environments and frontier evaluations
- ✦Cortex: contextual evaluation for production AI agents
- ✦Expert-demonstrated robotics training data
- ✦Benchmarks such as LongExtractionBench
- ✦Expert human data partnerships
- ✦Research lab on human data markets
- →Collecting human preference data for RLHF or model evaluation
- →Running academic behavioral or market research studies
- →Sourcing domain-expert data for specialized AI benchmarks
- →Earning side income as an AI trainer
- →Contributing expertise to improve AI
- →Flexible remote work for grads and experts
- →Gaining hands-on AI and prompt experience
- →AI labs sourcing domain experts for RLHF projects
- →Companies needing red-teaming of a new model
- →Teams building custom labeled training datasets
- →Domain experts (healthcare, legal, finance) earning remote pay for AI training work
- →Train and evaluate frontier AI models
- →Improve agent performance in production
- →Source expert human data for AI labs
- →Gather demonstration data for robotics