Annotation providers

Provides human-feedback and labeling services for generative AI and custom models as the AI-focused division of Apex CoVantage.

Provides human-validated data for model alignment, agent trajectories, speech, physical AI, and model evaluation.

Collects real-world human activity footage and teleoperation data, then prepares annotated training material for embodied-AI development.

Develops conversational audio datasets, annotation, voice-actor material, and speech-interaction research for teams building voice AI.

Combines multilingual and multimodal datasets, expert services, and AI platforms for model development and enterprise deployment.

Supplies physical-AI video datasets with annotations and structured signals such as pose, depth, and segmentation, alongside custom collection.

Prepares unstructured data and combines human validation, model oversight, and workflow orchestration to support operational AI systems.

Provides a platform for managing, curating, versioning, and annotating unstructured datasets. Teams can connect human feedback, model operations, and automated pipelines across image, video, audio, and other data.

Offers off-the-shelf AI datasets and custom collection and labeling services, including speech, vision, and multimodal material.

Offers a dataset marketplace plus custom collection, annotation, translation, and model-evaluation services for enterprise AI projects.

Now operating as TrustScale, e2f provides custom training datasets, expert annotation, and model evaluation. Its current offering covers multimodal data, language quality, factual verification, reasoning benchmarks, and safety review.

Combines multimodal data management and annotation software with managed collection and domain-expert annotation services.

Provides expert-led annotation and generative-AI workflows, including feedback, reasoning data, and agent evaluation through its tools and services.

Offers data services for generative, agentic, and physical AI, including custom training environments, collection, and model-safety evaluation.

Offers expert-produced reasoning annotations, preference examples, and reinforcement-learning evaluations aimed at robot learning and world models. Public service detail is limited to the official site’s description.

Collects, labels, transcribes, and evaluates text, audio, images, and video. Its services include ready-made datasets, custom collection, supervised fine-tuning examples, human preference feedback, and model red-teaming.

Processes robot and first-person recordings into timestamped action segments, reconstructed hand motion, and automated quality checks. Its pipelines assess visual quality and task completion in training and deployment footage.

Collects first-person activity data and enriches it with motion, geometry, contact, and scene information. Its robotics-focused services include hand and body tracking, sensor capture, and model evaluation.

Recruits and manages domain specialists for model evaluations, post-training examples, and independent annotation audits. Deliverables include preference comparisons, demonstrations, rubric scores, and quality-assurance reporting.

A talent marketplace and managed-service provider for AI data work. Teams can source specialists for annotation, model evaluation, preference feedback, and safety testing while retaining their existing tools.

Runs expert-led data and evaluation programs, supplies specialists, and collects embodied multimodal recordings. Its work includes professional-domain assessment, safety testing, multilingual benchmarks, and labeled robotics sensor data.

Provides expert annotation and evaluation services alongside its Syncronus collaboration platform. Work covers difficult reasoning, tool use, agent behavior, safety testing, and peer-reviewed specialist workflows.

Delivers human-verified annotation, data validation, and model evaluation for computer vision and multimodal AI.

Reviews AI training data against agreed criteria using AI judges calibrated and checked against human experts.

Offers AI data collection, annotation, and model-evaluation services across speech, healthcare, and other multimodal applications.

Combines multimodal annotation, data orchestration, human review, and evaluation tooling, including support for agent trajectories and RL environments.

Offers data collection, specialist post-training work, annotation, safety evaluation, and off-the-shelf datasets across language, vision, and physical AI.

Creates agent-training data, simulated environments, human feedback, and evaluations covering tool use, coding, and model safety.

Offers data collection, annotation, testing, and human-in-the-loop validation for generative and physical AI through its operations platform and contributor network.

Supplies first-person industrial footage enriched with process context and action labels for robotics and physical-AI systems.