Large-scale multilingual and multimodal datasets for training and extending foundation models, including conversational structure, long-tail knowledge, and real-world interaction patterns.
High-coverage public data for languages and regions that are underrepresented in licensed or synthetic datasets, enabling robust multilingual performance and evaluation.
Aligned text, image, video, audio, and document data for training and evaluating multimodal models in real conversational and social contexts.
Multimodal sensor and perception datasets for training and evaluating embodied AI systems, including vision, proprioceptive signals, and custom sensor data from real-world robotic environments.
Large-scale video datasets designed for training models on temporal reasoning, long-context understanding, and audiovisual dynamics across short- and long-form content.
Large-scale voice and audio datasets for training and evaluating speech recognition, multilingual speech models, and audio-language alignment.
Curated code corpora for training and evaluating code generation, code understanding, and software reasoning models across languages, frameworks, and real-world software repositories.
Specialized datasets for training and evaluating models in scientific, engineering, and technical domains, including peer-reviewed literature, textbooks, and domain-specific documents.
Real-world documents for training and evaluating document intelligence systems, including OCR, layout reasoning, table extraction, and structured content understanding.
Buyer-scoped datasets with configurable anonymization, filtering, modalities, and delivery formats aligned to internal research, legal, and infrastructure requirements.
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