DAI-Decentralized AI


DAI - Decentralized Artificial Intelligence infrastructure

What we are building

DAI = a new type of AI infrastructure where:


Global Context and Challenges

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1

Growing Energy Consumption

Coordination and connection to grids in Europe takes 2-10 years, so AI capacities cannot keep up with demand.

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2

Data Privacy

By 2030, approximately 75% of corporate data will be created and processed outside traditional data centers, closer to the user (edge).

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3

AI Market

The generative AI market is projected to grow to approximately 100 billion USD by 2030.

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4

Risk of Power Outage (Blackout)

Cyberattacks and aging infrastructure create a risk of cascading power outages, rendering mobile communications, the Internet, and digital services unavailable.

What is DAI?

A scalable, modular, and energy-efficient ecosystem:

DAI Node

AI module for everyone

Privacy-First

All sensitive workflows can run locally, with no mandatory cloud dependency.

All-in-One AI Workspace

Combines AI processing with content creation, publishing, and customer communication tools.


Energy Efficiency

Designed for minimal energy use, making it practical for continuous and solar-powered operation.

Standalone or Networked

Can operate fully on its own or connect to the DAI network for additional compute and distributed intelligence.

Services that Node can provide


Local AI Assistant

Provides private AI support for daily tasks such as document search, summarization, drafting, and Q&A.

Content Creation

Generates posts, captions, reels, and carousels, and can automatically publish them on schedule.

AI Customer Communication

Responds to comments and messages using a knowledge base, and can support consultations and sales using scripts.

Local Data Processing

Processes documents, video, and sensor data locally without sending sensitive information to the cloud.

DAI Hub

Energy-independent cluster

Green Energy

The hub can run on solar energy, which is primarily used for "digital" tasks, while surplus energy is stored in batteries or directed to the EV charging port.

Edge AI

Local data processing center with Edge AI:

  • Performs computations locally, without sending data to the cloud;
  • Connects to other clusters and nodes in a decentralized peer-to-peer network.

Smart Services

  • Encryption and distributed data storage, blockchain network
  • Decentralized communication channel (messenger/Meshtastic network)

Monetization

  • Monetization of surplus solar energy (EV charging with time/idle fees)
  • Can perform DAI network tasks and generate additional income

Services that Hub can provide


AI Assistant

Processing internal documents, customer support, information retrieval, creative solutions, research without transferring data to third parties.

Smart City

Monitoring traffic, parking spaces, environmental conditions, analyzing video streams locally and in real time, with full GDPR compliance, without sending to the cloud.

Communication and Data Storage

Communication and data access even during power outages (blackouts) or without mobile internet.

  • Data is duplicated across multiple nodes
  • Decentralized/Meshtastic messenger
  • Starlink or other satellite solutions

Energy Hub

Flexible load management with AI, stored energy can be directed to charging electric vehicles or other priority loads

DAI Network

Each node is an equal member of the network

Has a description of its capabilities

Exchanges load metrics

Automatically routes requests

Can split task flow among multiple nodes

How does it work?

Decentralized AI Learning: Federated + P2P Training

DAI Monetization Paths

Network Subscription

Monthly fee for services

Usage-based Model

Payment according to actual usage

B2B Packages

Ready-made solutions at a fixed price.

B2G Contracts

Long-term agreements with government agencies

Green Hub

Revenue from EV charging stations

Marketplace

Renting edge computing for third parties


Competitors and Analogues



DAI Positioning (How We Differ)

Self-sufficiency

Each node/cluster pays for itself through the revenue it generates.

Competitiveness

Competitive prices result from energy efficiency / distributed task execution

Eco-friendliness

Part of AI tasks are performed during periods of excess solar generation

Blockchain network

Transparent accounting of task execution and reward distribution among network nodes.

Data Privacy

Encrypted and distributed data storage

User Convenience

Focus on adapting models to user needs, no technical skills required

Value for the Country and Region

Monetization of Green Energy

Surplus solar energy is converted into valuable digital services

Sovereign LLM-model for the Country/Region

Training and deployment of a proprietary decentralized LLM-model adapted to the language, laws, and data of the region.

Digital Sovereignty

Local infrastructure provides full control over data, resilience to external interference, and autonomy from global providers.

Rapid Modular Scaling

Easily implemented without significant initial investments, does not require laying power lines/upgrading substations.

Support for Green Transition

Combines decarbonization goals with digital transformation, creating synergy between environmental and technological initiatives of the EU.

Service Resilience

Backup channel for communication/processing/caching/storage during crises (poor internet, provider failures, blackouts).

Energy Independence and Autonomy

Minimal dependence on network prices/risks; during blackouts, hubs become local "islands" of power for critical needs.

Self-sufficiency and Income

A cluster is a profitable asset, not just a budget expense: digital services + energy/charging generate funds for the budget/development fund.

Innovation

Installing such a cluster positions the community/region among innovators and technological pioneers, enhancing prestige and recognition.

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