Backed by EuroHPC · LUMI AI Factory

Your AI. Your data. Shared intelligence.

DAI is developing decentralized, energy-aware AI Infrastructure that creates a peer-to-peer network of autonomous edge AI Nodes that provide local AI services, distributed model execution, and privacy-aware collaborative learning.

A glowing network shaped like a brain, ringed by connected nodes

From isolated devices to cooperative intelligence

A small AI system can operate locally and autonomously, but its computing resources are limited.

DAI is a technology that brings together the computing power of multiple small AI systems into a single distributed supercomputer — a Collective Superbrain.

This enables them to run large language models collaboratively, maintain a shared understanding of the world by exchanging data through a peer-to-peer network, and do all of this without relying on a central server.

DAI-MESH Network

Peer-to-peer coordination, private deployments, adaptive routing, fault recovery and control at the edge.

Explore Mesh

Distributed Digital Twin

Autonomous sensors and AI nodes exchange structured observations to maintain a shared understanding of physical environments.

Explore Digital Twin

Distributed LLM

Split model execution and cooperative compute across multiple nodes, including workloads larger than a single device can host.

Explore Distributed LLM

Why it matters

AI is powerful. Its infrastructure is fragile.

The problem

Today's AI infrastructure relies heavily on centralized data centers and cloud services. This dependence creates vulnerabilities to cyberattacks, infrastructure failures, power grid disruptions, and cascading outages that can interrupt access to AI services.

At the same time, the rapid growth of AI is driving unprecedented demand for electricity, while limited grid capacity, high infrastructure costs, and lengthy approval processes are slowing the deployment of new AI computing capacity.

The DAI solution

DAI is building decentralized AI infrastructure where computing is no longer dependent on a single central data center. Instead, workloads are distributed across autonomous AI devices, local computing nodes, and energy-independent clusters connected through a peer-to-peer network.

DAI's modular, peer-to-peer architecture enables AI computing capacity to scale by connecting additional nodes rather than relying on the construction of traditional centralized data centers.

Energy-aware workload distribution and the ability to operate nodes using independent or renewable power sources can further reduce dependence on centralized infrastructure, ease deployment in power-constrained locations, and improve resilience.

External validation

With the support of the European Union and EuroHPC.

DAI received a EuroHPC allocation on LUMI, one of Europe’s fastest supercomputers.

This grant turned an architecture that previously existed only on paper into real MVP nodes and enabled experiments that can help bring the DAI Network to scale.

Thanks to access to supercomputing resources, the team is working on:

Building the Distributed Model Layer: splitting large AI models across multiple nodes and enabling recovery when one of those nodes goes offline.
A network simulator with thousands of virtual peer-to-peer devices: testing unstable connections, node churn, and partial network outages.
Federated and Split Learning experiments across heterogeneous nodes, including devices running on battery power.

This non-dilutive R&D support validates the project as an innovative AI infrastructure initiative with significant potential for further development — not simply an early-stage commercial idea.

Off-grid DAI Node with a LiFePO4 battery and solar panels behind it

We built our first working off-grid DAI Node — powered by its own battery and rechargeable from solar panels.

With Starlink connectivity, it can operate privately and locally or connect to the DAI Network, keeping AI available even during power outages.

The same low-power, renewable-energy setup can also help make Green Mode compute cheaper across the network.

DAI at Web Summit 2026 as part of Slovenia’s national delegation in Lisbon

SPIRIT Slovenia / Web Summit 2026

Selected by SPIRIT Slovenia to represent Slovenia as part of the national delegation at Web Summit 2026 and to be presented at the Slovenian national stand.

This non-dilutive R&D support validates the project as an innovative AI infrastructure initiative with significant potential for further development — not simply an early-stage commercial idea.

Where we are

March 2026

DAI d.o.o. founded

DAI d.o.o. is established in Slovenia to continue the development and commercialization of decentralized AI infrastructure.
Summer 2026

EuroHPC allocation on LUMI

DAI receives access to LUMI through the LUMI AI Factory / EuroHPC program. Work begins on the decentralized DAI Network, distributed AI architecture, and DAI’s own AI models.
Summer 2026

First autonomous DAI Node MVP

The first working autonomous DAI Node prototype is built — operating on battery power, rechargeable from solar panels, and capable of running AI locally or connecting to the network.
Summer 2026

Distributed Model Layer on LUMI

Large-scale R&D begins on splitting large AI models across multiple nodes, automatic failure recovery, network simulation, and Federated & Split Learning across heterogeneous devices.
Next · planned

Physical multi-node DAI-MESH Beta

Measure distributed inference, state synchronization, energy and recovery on real hardware.

Early access / network beta

Help test the first physical DAI-MESH network.

We are progressing from simulations and prototypes toward real-world distributed inference. Join the early interest list as a user, compute contributor or private-network partner.