AI systems are trained on enormous amounts of data and powered by vast compute resources but the people and institutions providing those inputs rarely receive credit or compensation for their knowledge. The value is captured by a handful of corporations that control the resulting models. Gaia Labs, co-founded by CEO Matt Wright, Shashank Sripada and Sydney Lai aims to change that. Its premise is straightforward: anyone who contributes something of value to an AI system, whether its data, compute or expertise, should remain the owner of their contribution and share in the rewards when that system is used. Gaia’s infrastructure tracks usage and distributes rewards automatically. Gaia doesn’t retroactively redistribute past training material. Instead, it creates infrastructure for the future, where contributors decide whether to participate and maintain visibility and control. Gaia provides modular building blocks for compute, identity, data rights and payments. Developers select or design an AI agent template, connect their data, and decide where to run it—on Gaia’s distributed network or their own infrastructure. From there, Gaia automates compliance, identity verification, and payments. Once deployed, agents perform tasks, serve users, and log usage. Rewards are shared across contributors, whether they provided compute, data, or domain expertiseGaia differentiates itself by offering end-to-end infrastructure, removing the need for developers to piece together multiple tools. For startups, Gaia means freedom to build without corporate gatekeepers. For enterprises, it enables responsible training of AI on proprietary or sensitive data. For individuals, it offers recognition and rewards for contributions—whether from a home GPU or a specialized dataset.