AI Training Data
Every AI system learns from data. The quality, diversity, and precision of that AI training data determines what a model can do, what it cannot do, and how reliably it does it under real-world conditions. Appen has been building AI training data for 30 years, for the companies that defined search, the platforms that built the first neural ranking models, and the research teams training today's frontier models.
Our six Data Product pillars cover every major training data requirement across the AI development lifecycle: from frontier model alignment and multimodal perception to agentic workflow training, model evaluation, and speech and audio collection.
Data Products
Frontier Model Alignment
Expert-validated data for the highest-stakes stage of model development. Chain-of-thought reasoning traces, subject matter expert RLHF, supervised fine-tuning demonstrations, adversarial red teaming, and knowledge rubric design for teams training models where accuracy and safety are non-negotiable.
Agentic AI
Training data for agents that act, not just respond. Golden trajectory creation, verifier design, RL environment builds, RAG evaluation, and failure mode taxonomy for teams at the frontier of autonomous AI systems.
Speech & Audio
End-to-end speech data collection and annotation across 500 global locales. Expressive TTS synthesis, multi-speaker transcription, acoustic scene detection, and code-switched dialectal speech for teams building the next generation of voice AI.
Multimodal AI
Data for AI systems that see, hear, and understand across modalities simultaneously. Vision-language model alignment, audio-visual language sync, and video action recognition for teams training multimodal language models.
Physical AI
Data for AI systems that move and interact with the physical world. LiDAR annotation, sensor fusion, biometric collection, in-cabin automotive intelligence, and world model data for teams building embodied and physically-grounded AI.
Model Integrity & Evaluation
Independent evaluation data to ensure deployed models are accurate, unbiased, and safe. Hallucination benchmarking, A/B arena testing, regulatory audit support, bias detection, and continuous monitoring for teams that need evidence their model is ready.
Off-the-Shelf Datasets
Not every project requires custom collection. Appen's pre-built dataset catalogue covers speech, image, video, and text across 80+ languages, with clear provenance and licensing for immediate integration.
Selfie image and video collection
Collection of 2,938 selfie images and videos from 70 participants, capturing varied facial expressions across 1,566 recording sessions.
Action videos
281 videos of participants and animals completing prompted actions, e.g. zipping a jacket or drinking a beverage.
Product labels
54,350 annotated product label images spanning food, health & beauty, and pet supplies, with bounding box and text transcription.
Why Appen
Data annotation quality and contributor expertise are the two variables that most determine training data value. Appen's global network spans 170 countries, includes verified domain specialists across 50 fields, and operates the quality management infrastructure required for safety-critical and frontier-grade data programmes. Our independence from any single AI platform means your training data programme is never constrained by a vendor's own model interests.
Kickstart your AI Journey
Our team offers customized solutions to meet your specific AI data needs, providing in-depth support throughout the project lifecycle.