Meaningful work, organized into clear categories.
Every task type below supports real AI evaluation and data quality work — never ad clicks, captchas, or spam.
AI Response Evaluation
Assess AI-generated responses for accuracy, helpfulness, and safety.
Data Annotation
Label structured and unstructured data to train and improve AI models.
Text Classification
Sort text into categories based on topic, intent, or content type.
Sentiment Analysis
Judge the tone and sentiment expressed in written content.
Grammar Correction
Review and correct grammar, spelling, and phrasing in text samples.
Summarization
Evaluate or refine summaries for accuracy and conciseness.
Translation Review
Check translated content for accuracy, fluency, and cultural nuance.
Image Annotation
Tag, label, and categorize images to support computer vision models.
Information Extraction
Pull structured facts and entities out of unstructured content.
Reasoning Evaluation
Review step-by-step reasoning for logical soundness and correctness.
Dataset Quality Review
Audit existing datasets for consistency, accuracy, and completeness.
Human Feedback
Provide structured feedback that helps align AI behavior with human intent.