Human data for frontier AI
The world’s leading AI models are built on more than algorithms, they’re built on human expertise. We deliver the expert-validated data that trains frontier models, ensuring AI systems understand nuance, context, and complexity at scale.
Six specialised capabilities, each purpose-built for a critical dimension of modern AI development.
01
Frontier Alignment
CoT reasoning traces, SME RLHF, SFT demonstrations and adversarial red teaming for the world’s most capable models.
RLHF
Reasoning
Safety
02
Agentic AI
Golden trajectories, RL environment design, failure mode taxonomy and SWE-driven deep evaluation for autonomous agents.
Trajectories
RL Envs
Evaluation
03
Speech & Audio
Expressive TTS synthesis, emotion detection, dialectal speech and paralinguistic labelling across 500+ global locales.
TTS
ASR
Localisation
04
Multimodal AI
Fine-grained VLM training data, image-text contrastive pairs, spatiotemporal video annotation, audio-visual alignment and structured document labelling for models that reason across heterogeneous input modalities.
VLM
Multimodal AI
MLLM
05
Physical AI
LiDAR point cloud annotation, multi-camera sensor fusion, robot demonstration trajectories, world model rollouts and embodied interaction logs for AI systems operating in unstructured physical environments.
Robotics
LiDAR
World Models
06
Model Integrity
Hallucination benchmarking, regulatory audits, bias detection and continuous monitoring to ensure your models are trusted.
Evaluation
Safety
Compliance
30 Years of Pioneering Data
Trusted expertise at the intersection of human intelligence and AI innovation
1996
Early NLP Systems
Speech recognition and language processing — Appen's first steps in building human-labeled datasets for AI.
2003
Search Relevance
Human evaluation for search quality at scale, powering the first generation of web search ranking models.
2006
Machine Translation
Statistical translation models requiring multilingual human annotations across 100+ language pairs.
2012
AlexNet Era
Deep learning for computer vision — image annotation and bounding box labeling at industrial scale.
2017
Transformer Models
Attention mechanisms and BERT demanded high-quality sentence-level semantic understanding data.
2020
GPT-3
Large language model training required vast, carefully curated, diverse human-generated text datasets.
2022
ChatGPT & RLHF
Human feedback alignment — our annotators trained reward models that shaped modern conversational AI.
2024
Multimodal Foundation Models
Vision, language, and reasoning combined — powering the next generation of frontier AI systems.
2025
Agentic AI
Agentic AI went viral bringing scalable agents to local hardware.
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