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.


Akai Space

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Akai Space

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