We don’t just support AI, we build the data infrastructure that powers it. From customer experience to foundation models, autonomous systems to physical AI, we operate as one partner across every layer of the stack.
RLHF, red-teaming, evaluation, sensor fusion and teleoperation are the human-in-the-loop work that makes AI accurate, safe and production-ready, delivered at enterprise scale across 13 countries and 28 languages.
With 17.5K+ people and zero vendor lock-in, we are architecture-agnostic and work with every major AI lab and enterprise team, because we are not owned by any of them.
The bottleneck has moved to high-quality, human-validated data. We deliver it as recurring, production-grade infrastructure.
Not owned by, invested in or aligned with any foundation model company, and architecture-agnostic by design.
A workforce already deployed for simultaneous multilingual delivery with consistent quality and audit trails.
Three-layer QA: expert annotation, independent peer and model review, and sampled audit with full traceability.
Enterprise security, privacy compliance and full audit trails, proven across financial services, healthcare and telecom.
Annotera handles data collection, annotation and generative AI operations. Roborax handles physical AI and robotic training data.
Text, image, video, audio and sensor data, including LiDAR, depth and GPS, captured in controlled and real-world settings.
Classification, NER, bounding boxes, segmentation, video tracking, audio transcription and 3D point-cloud annotation.
RLHF datasets, preference ranking, instruction tuning, evaluation, red-teaming, safety datasets and benchmarks.
Roborax teleoperation demonstrations, sensor fusion annotation, LiDAR processing and edge-case curation.
Unified text, image, audio and video datasets for vision-language models and multimodal AI research.
We manage the program, workforce, quality and compliance from collection to delivery of production-ready data.
From foundation models to autonomous systems, we deliver training and evaluation data built for each sector’s requirements.
RLHF, instruction tuning, evaluation benchmarks, red-teaming and safety datasets for foundation model training.
Medical image annotation, clinical NLP, speech transcription and LLM training data for healthcare AI.
Image, video and LiDAR annotation, sensor fusion and edge-case curation delivered at scale.
Document annotation, NLP datasets, compliance data and decision-trail training sets for financial AI.
Teleoperation data, manipulation datasets, sensor annotation and warehouse automation training.
Speech annotation, sentiment analysis, conversational AI training and agent-assist data pipelines.
Tell us about your models, modalities and quality bar. We’ll show you how our AI data infrastructure can support your roadmap and respond within one business day.
Guides for teams building accurate, safe and production-ready AI.
What AI labs and enterprise teams ask before choosing a data partner.
It covers the full AI data lifecycle: data collection, multimodal annotation, generative AI data operations such as RLHF and red-teaming, physical AI and robotics data, and end-to-end managed delivery.
Annotera handles data collection, annotation and generative AI operations. Roborax handles physical AI, including teleoperation, sensor fusion and robotic training data. Together they cover the entire data supply chain.
No. We are not owned by, invested in or aligned with any foundation model company. We are architecture-agnostic and work with any model, in-house stack or evaluation framework, and your training data stays yours.
Every project runs through three layers: expert annotation to a project-specific rubric, independent peer and model review, and sampled audit with full traceability, delivering 99.2% first-pass accuracy.
