The Machines Are Listening: AI Inference Launches on Datagram Nodes
AI inference is no longer theoretical. It’s running — live — on Datagram’s decentralized node network. Our nodes don’t just store and secure data anymore. They compute. They process. They think. And for the first time, intelligence lives at the edge — owned and operated by the people, not platforms.
The Machines Are Listening: AI Inference Launches on Datagram Nodes
Today marks a milestone: Not just for Datagram, but for the future of decentralized intelligence.
With the launch of our AI inference layer, Datagram nodes now do more than host content, route data and secure the edge. They think now. They’ve become part of a distributed neural mesh, capable of running AI models in a trustless, decentralized environment. It’s live. It’s running. And it’s ready to use.
Whether you're spinning up an AI assistant, a role-based concierge or something more custom, your agent's logic and learning will now run on infrastructure you can actually own. It’s a new level of autonomy, for users, developers and the intelligence you create.
You can test a basic version of this right now at demo.datagram.network which works on nodes. This isn’t a centralized test environment or staged rollout. It’s real inference, happening on the live Datagram network, powered by the same Full Core Nodes that form the backbone of our system.
And this is just the start.
As nodes provide inference services, they earn a new reward: "AI", a temporary, soul-bound utility token that tracks their contribution to distributed compute. At the end of each day, those tokens automatically convert into $DGRAM, the core currency of the Datagram ecosystem. No staking. No complicated setup. Just uptime, contribution and impact.
Decentralized infrastructure doesn’t mean much unless it actually does something. Hosting idle capacity isn’t enough. Our vision is different: a living network where intelligence moves, evolves and scales, without permissions, gatekeepers or intermediaries. Datagram nodes are no longer just participants, they’re active contributors. They run AI. They train AI. And they get rewarded for it.