Data Annotation Companies

The directory of data annotation companies. Compare top AI data labeling firms, read worker reviews, and browse data annotation jobs hiring remote workers worldwide.

Featured data annotation companies

  • Revelo — Human data for LLM training, code-output annotation, SFT, RLHF, DPO code training data
  • Mercor — AI-powered platform for talent sourcing, data annotation for LLMs (especially video-based content), multi-turn data
  • Micro1 — micro1 is a San Francisco AI training-data company that recruits vetted subject-matter experts — software engineers, PhDs, physicians, lawyers and financial analysts — to build ev…
  • Ethos — Ethos (AskEthos) is an AI expert network that matches experienced professionals, including lawyers, clinicians, finance analysts, engineers and researchers, with paid AI model tra…
  • AISpotters — Artificial Intelligence, Machine Learning, Data Labeling, Data Collections, Image Annotation, Audio Annotation, Video Annotation
  • Acgence — AI Data Collection Services
  • Alectio — Machine Learning-Driven Data Curation, DataPrepOps platform
  • Aligned AI — Broad/Unclear specialization
  • Alignerr — Data labeling, model evaluation, aligning AI models
  • Anthromind — High-quality dataset development for AI model performance, complex data requirements
  • Appen — Data annotation services for AI and ML models, data collection, evaluation, image, audio, and video annotation
  • Blomega — Broad/Unclear specialization

See all 82 companies →

Frequently asked questions

What exactly is data annotation, and why is it important?
Data annotation is the "teaching" phase of Artificial Intelligence. By adding labels or tags to raw data, you provide the ground truth that AI models use to learn patterns. Without high-quality human annotation, AI systems wouldn't be able to recognize speech, identify objects, or generate human-like text accurately.
What skills or qualifications do I need to become a data annotator?
Most roles require high attention to detail, strong linguistic skills, and the ability to follow complex labeling guidelines. For general tasks, a high school diploma and computer literacy are standard. However, "Expert" annotation roles may require a background in fields like law, medicine, or software engineering to ensure the labels are technically accurate.
Is this a remote-friendly role, and what does the workload look like?
Yes, the majority of data annotation positions are remote and offer flexible hours. Depending on the project, you might work on a task-by-task basis (crowdsourcing) or as a dedicated part-time or full-time contractor. This makes it an ideal role for those seeking a flexible schedule that fits around other professional or personal commitments.
How is the quality of my work measured?
Quality is typically measured through "Gold Standard" tasks (hidden tests with known answers) and "Inter-Annotator Agreement," where multiple people label the same item to see if they agree. Consistently high accuracy scores are usually required to remain on a project or to be promoted to a "Reviewer" or "Quality Auditor" role.