> For the complete documentation index, see [llms.txt](https://gata-1.gitbook.io/gata-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://gata-1.gitbook.io/gata-docs/architecture/editor.md).

# Technical Architecture

Gata’s DataAgent system enables the decentralized production of large-scale AI-driven data for AI training by aggregating idle compute resources from participants.

The data generation process consists of three core components: input data, AI computation, and output data:

{% stepper %}
{% step %}
Input data is stored on BNB Greenfield, a decentralized storage chain within the BNB ecosystem, to ensure persistent availability and broad accessibility.
{% endstep %}

{% step %}
Participants use their local compute resources to perform AI computations on the retrieved input data, processing it into valuable AI outputs.
{% endstep %}

{% step %}
Output data and proofs of contribution are anchored back onto BNB Greenfield, securing provenance, ownership, and integrity through decentralized storage.
{% endstep %}
{% endstepper %}