Purpose-built data for frontier AI labs. Each solution is backed by real project metrics, verified research citations, and Claru's expert human annotation methodology.
End-to-end data collection and annotation for the highest-demand AI training modalities.
500K+ licensed egocentric video clips for robotics and embodied AI. Enriched, QA-verified, delivered weekly. See how we compare to Ego4D and EgoDex.
Learn more →Expert human red teaming for AI models — structured adversarial testing that satisfies EU AI Act Articles 55 and 99. 241K+ safety annotations delivered.
Learn more →Expert human preference data for video generation model training. 976K+ quality assessments, 39K pairwise evaluations across 51 model configs. RLHF-ready.
Learn more →Custom vision-language-action datasets with paired video and action labels. 386K+ clips, sub-16ms sync. Built for OpenVLA, RT-2, and pi-zero architectures.
Learn more →Targeted solutions for specific data challenges in robotics and model alignment.
Why crowdsourced RLHF fails for code and specialized domains. Claru delivers expert annotation with 976K+ assessments and statistically rigorous evaluation.
Learn more →Why open manipulation datasets fail production robotics and how Claru collects custom trajectory data across 386K+ clips and 10,000+ hours of synchronized capture.
Learn more →Bridge the sim-to-real gap with targeted real-world data collection. Claru delivers diverse physical-world datasets that reduce domain transfer failures by grounding simulation in reality.
Learn more →Scale teleoperation data collection beyond lab constraints. Claru delivers diverse operator demonstrations across real environments — 386K+ clips captured with managed global contributors.
Learn more →Research-backed decision guides for teams evaluating data strategies.
Compare Open X-Embodiment, DROID, and AgiBot World against custom data collection for robotics. Scale, task coverage, and quality trade-offs explained.
Learn more →Crowdsourced RLHF introduces incorrect preference pairs that degrade reward models. Compare failure modes, costs, and expert alternatives for code and math.
Learn more →EU AI Act Articles 5, 55, and 99 mandate adversarial testing for AI systems. Enforcement timeline, fine structure, and the red teaming data you need to comply.
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