Akai Space

Akai Space builds infrastructure for scaling AI data. We began by solving a fundamental problem in AI development: creating reliable systems for large-scale human data collection and annotation through distributed workforce operations. That foundation now extends into the next frontier of AI infrastructure: embodied intelligence. As vision-language-action (VLA) models and physical AI systems begin entering their scaling era, the bottleneck is no longer just model architecture--it is data infrastructure. Unlike language models, embodied AI still lacks scalable, repeatable systems for collecting, processing, and operationalizing real-world interaction data. Akai Space is building that stack. Our work spans the full embodied data infrastructure loop: * Egocentric data capture systems * Large-scale field data operations * Data processing and embodied training pipelines * Research on scaling data for physical AI systems Alongside this, Akai Earn serves as our distributed human data operations layer--enabling scalable annotation, collection, and workforce orchestration across AI data workflows. Our thesis is simple: The next major breakthroughs in AI will come not just from better models, but from better infrastructure for generating the right data. We're building the systems that make that possible.