Ratio1 is a decentralized AI meta-operating system that enables trustless, privacy-preserving machine learning and AI inference across heterogeneous edge devices. Built on the Ratio1 DNA (Decentralized Neuro-symbolic Autonomous processing) framework, our platform combines blockchain-secured container orchestration, distributed storage, and federated computing to democratize AI infrastructure.

Key Technologies:

• Deeploy: Decentralized container orchestration with smart-contract-secured scheduling
• R1FS: Encrypted, sharded distributed file system with zero single points of failure
• J33VES: Multi-foundation model framework for open-weight LLMs and AI agents
• ChainDist: Fault-tolerant distributed job execution across heterogeneous nodes
• EDIL: Encrypted Decentralized Inference and Learning with homomorphic encryption
• dAuth: Blockchain-validated decentralized authentication and identity management
• PoAI Escrow: Proof-of-AI oracle-verified trustless service payment system

Democratize AI and machine learning by eliminating infrastructure barriers through decentralized edge computing, enabling instant deployment, reducing operational costs by 10-100x, and creating economic incentives for distributed compute providers.

The Ratio1 DNA (Decentralized Neuro-symbolic Autonomous processing) framework provides a distributed AI runtime that enables:

• Blockchain-Validated Compute: Smart-contract-secured task scheduling and verification
• Heterogeneous Edge Network: CPU, GPU, TPU, and Apple MPS support across x86, ARM64, and RISC-V architectures
• Privacy-Preserving AI: Homomorphic encryption (EDIL) for training and inference without exposing data
• Zero-DevOps Deployment: Automated container orchestration via Deeploy with load balancing and fault tolerance
• Decentralized State Management: CSTORE in-memory database for distributed application coordination

Deeploy – Trustless container orchestration replacing centralized Kubernetes with smart-contract-secured scheduling, enabling automated deployment across heterogeneous edge nodes.

R1FS – Distributed file system with encryption, sharding, and redundancy. Includes Local Endpoint for legacy application integration with decentralized storage.

ChainDist – High-performance distributed job execution framework with CSTORE integration for state management and fault-tolerant scheduling.

J33VES – Multi-model AI agent framework supporting open-weight LLMs (Llama, Mistral, etc.) with RAG-as-a-Service capabilities.

EDIL – Encrypted Decentralized Inference and Learning framework enabling privacy-preserving model training and inference through homomorphic encryption.

Genesis Node Deed (GND) – Foundational validator node operated by Ratio1 Foundation, bootstrapping network consensus.

Master Node Deeds (MND) – Infrastructure nodes for development teams and validators, providing core ecosystem services (30+ month commitment).

Node Deeds (ND) – Public edge nodes enabling individual operators to provide compute resources and earn R1 token rewards.

🔬 Researchers & Academia

# Clone the SDK and explore research examples
git clone https://github.com/Ratio1/ratio1_sdk.git
cd ratio1_sdk/examples

# Access whitepaper and technical documentation
# Visit: https://ratio1.ai/whitepaper

💻 Application Developers

# Install SDK and start building
pip install ratio1

🌐 Node Operators

# Method 1: Quick Start with Docker (Recommended for Single Nodes)
docker run -d --rm --name r1node --platform linux/amd64 --pull=always \
  -v r1vol:/edge_node/_local_cache/ ratio1/edge_node:develop

Method 2: Multi-Node GPU/CPU Deployment with r1setup (Recommended for Scale)

For large-scale GPU deployments, r1setup provides an SSH-based multi-host deployment tool with automated Ansible workflows.

Features:

• Automated GPU driver installation (NVIDIA CUDA support)
• Multi-node deployment from a single control machine
• SSH-based configuration (no manual setup on each node)
• Supports heterogeneous hardware configurations

📖 Follow the complete step-by-step tutorial: Introducing Multi-Node Launcher (r1setup) - GPU Deployment at Scale Made Simple

GitHub Repository: https://github.com/Ratio1/r1setup

Method 3: Edge Node Launcher (GUI - Currently in Major Overhaul)

Note: The graphical Edge Node Launcher is undergoing significant improvements.

Download legacy versions: https://downloads.ratio1.ai/ Available for Windows, macOS, and Linux

Minimum Configuration:

• CPU: x86-64 or ARM64, 4+ cores (virtual cores supported)
• RAM: 16GB (32GB recommended for AI workloads)
• Storage: 100GB SSD (500GB+ for storage nodes)
• Network: 100+ Mbps stable connection
• OS: Ubuntu 20.04+, Debian 11+, macOS 12+, Windows 11 with WSL2
• Runtime: Docker 24+ or Podman 4+

Recommended for Production:

• CPU: 8+ cores with AVX2/AVX-512 support
• GPU: NVIDIA GPU (CUDA 11.8+), Apple Silicon (MPS), or AMD GPU (ROCm 5.6+)
• RAM: 32-64GB
• Storage: 1TB+ NVMe SSD for R1FS nodes

• Zero-Config Orchestration: Deploy containerized AI models via Deeploy without Kubernetes expertise
• Auto-Scaling: Dynamic resource allocation across edge nodes based on demand
• Multi-Model Serving: Simultaneous deployment of multiple LLMs, vision models, and custom ML pipelines
• Template Library: Pre-configured deployments for popular frameworks (PyTorch, TensorFlow, JAX, ONNX)

• Homomorphic Encryption: EDIL framework enables encrypted model training and inference
• Federated Learning: Distributed training without centralizing sensitive data
• Zero-Knowledge Proofs: Verify computation integrity without revealing model parameters
• Secure Enclaves: TEE (Trusted Execution Environment) support for sensitive workloads

• Multi-Architecture: Native support for x86-64, ARM64 (Tegra, Raspberry Pi), and RISC-V
• GPU Acceleration: NVIDIA CUDA, AMD ROCm, Apple Metal Performance Shaders (MPS)
• Adaptive Scheduling: ChainDist intelligently distributes jobs based on node capabilities
• Fault Tolerance: Automatic failover and job migration on node failures

• Smart Contract Validation: All compute tasks verified on-chain via PoAI consensus
• Cryptographic Signatures: dAuth provides tamper-proof identity and access management
• Immutable Audit Trails: Complete traceability of all operations and transactions
• Trustless Payments: Escrow-based settlement with oracle verification of task completion

• Multi-Protocol Support: MQTT, RTSP, HTTP/S, WebSocket, gRPC, ODBC, CSV, Parquet
• IoT Integration: Native support for sensor networks and edge devices
• Stream Processing: Real-time data pipelines with sub-100ms latency
• Batch Processing: ETL workflows for large-scale dataset transformation
• R1FS Storage: Decentralized persistence with encryption and redundancy

• Data Preprocessing: Distributed ETL and feature engineering across nodes
• Model Training: Federated and encrypted learning via EDIL framework
• Inference Serving: Load-balanced, auto-scaled model deployment
• Post-Processing: Business logic execution and decision automation
• Monitoring: Real-time performance metrics and model drift detection

• Message Queue: Distributed MQ system for asynchronous node coordination
• REST API: OpenAPI-compliant interfaces for external integrations
• gRPC: High-performance RPC for inter-node communication
• WebSockets: Real-time bidirectional data streaming
• Load Balancing: Dynamic traffic distribution with health checks and failover

The R1 token is the native utility token powering the Ratio1 ecosystem, with a maximum supply of 161,803,398 tokens (derived from the golden ratio φ).

Token Utility:

• Compute Payments: Pay for AI inference, training, and storage services
• Node Staking: Stake R1 to operate nodes and validate transactions
• Governance: Vote on protocol upgrades and ecosystem proposals
• Developer Rewards: Earn R1 for contributing to open-source components

Economic Model:

• 70% Circulating: Node operator rewards, developer grants, ecosystem growth
• 15% Foundation Reserve: Long-term development and research funding
• 10% Team & Advisors: 48-month vesting schedule
• 5% Early Contributors: 24-month vesting schedule

Deflationary Mechanisms:

• Burn on License Purchase: 20% of Node Deed sales permanently removed
• Transaction Fees: 50% of network fees burned quarterly
• Liquidity Provision: 50% of license revenue directed to DEX liquidity pools

For Node Operators (R1OPs)

• Deploy edge nodes and earn R1 token rewards for compute provision
• Participate in network governance and protocol decisions
• Join the Master Node program for enhanced infrastructure roles

For Developers

• Build decentralized AI applications using the Ratio1 SDK
• Contribute to open-source repositories and earn developer grants
• Create application templates for the community marketplace
• Participate in hackathons and tutorial series

For Researchers & Academia

• Collaborate on distributed AI and privacy-preserving ML research
• Access the network for computational experiments and datasets
• Co-author papers on decentralized computing and blockchain AI
• Apply for research grants and joint projects

For Enterprises

• Migrate cloud workloads to cost-effective decentralized infrastructure
• Deploy white-label AI solutions powered by J33VES framework
• Integrate existing applications with R1FS and CSTORE
• Become a Cloud Service Provider (CSP) partner

Documentation & Learning

• 📖 Official Documentation – Comprehensive guides and API references
• 🎓 Tutorial Series – Video courses, hands-on workshops, and sample applications
• 📚 Technical Whitepaper – Academic publications and technical documentation
• 🛠️ Multi-Node Deployment – r1setup guide for GPU deployments

Community Channels

• 🌐 Website – Latest news and announcements
• 💬 Discord – Developer discussions and technical support
• 🐦 Twitter – Updates and ecosystem highlights
• 📧 Email – Direct support for partnerships and integration

Ratio1 is built on rigorous academic research in distributed systems, privacy-preserving machine learning, and blockchain consensus mechanisms.

Published Research Areas:

• Decentralized container orchestration and job scheduling
• Homomorphic encryption for distributed AI workloads
• Federated learning across heterogeneous edge devices
• Blockchain-based trustless compute verification (Proof-of-AI)
• Zero-knowledge proofs for privacy-preserving model validation

Academic Collaborations:

• Joint research projects with universities on distributed AI
• Open dataset contributions for decentralized ML benchmarking
• Conference publications (IEEE, ACM, and domain-specific venues)
• Graduate student internships and research fellowships

Upcoming Focus:

• Quantum-resistant cryptography for post-quantum security
• Advanced ZKP integration for enhanced privacy guarantees
• Cross-chain interoperability and multi-blockchain AI orchestration
• Energy-efficient consensus mechanisms for sustainable AI

📄 View our technical whitepaper and documentation at ratio1.ai/whitepaper

Ratio1's decentralized architecture delivers significant environmental benefits:

Carbon Footprint Reduction:

• 10-100x lower energy consumption vs. centralized data centers through efficient edge utilization
• Reduced cooling requirements: Distributed nodes eliminate massive HVAC systems
• Device reuse: Transform existing consumer hardware into productive AI infrastructure
• Renewable energy: Enable node operators to leverage local solar, wind, and green energy

Resource Optimization:

• Intelligent job scheduling minimizes idle compute time
• Dynamic power management adjusts resource usage based on workload
• Network-aware task distribution reduces data transfer overhead
• Shared infrastructure eliminates redundant hardware procurement

Sustainability Goals:

• Achieve carbon-neutral network operations by 2026
• Incentivize renewable-powered nodes through enhanced R1 rewards
• Publish quarterly environmental impact reports
• Support green computing research initiatives

2025 Major Milestones:

• ✅ Mainnet Launch: Deeploy v1, R1FS v1, ChainDist v1, J33VES v1 (July 2025)
• 🚀 PoAI Escrow v1: Trustless payment settlement (August 2025)
• 🔐 dAuth v2: Enhanced decentralized authentication (September 2025)
• 🤖 Automated Edge Nodes: Fully autonomous node software (December 2025)
• 🏗️ AI-for-Everyone Toolkit: Low-code AI application builder (December 2025)

2026 Goals:

• Multi-architecture support (ARM64, RISC-V, Apple MPS native)
• Application Marketplace for AI/ML solutions
• International CSP Conference and community hackathons
• Quantum-resistant cryptography and ZKP integration
• Large-scale enterprise application deployments

📋 View the complete roadmap: ROADMAP.md

All Ratio1 open-source repositories are licensed under the Apache 2.0 License, promoting open collaboration while protecting intellectual property rights.

Key Terms:

• Free for commercial and non-commercial use
• Modification and distribution permitted
• Patent grant included
• Attribution required

If you use Ratio1 in your research or applications, please cite our work:

@inproceedings{Damian2025CSCS,
  author    = {Damian, Andrei Ionut and Bleotiu, Cristian and Grigoras, Marius and
               Butusina, Petrica and De Franceschi, Alessandro and Toderian, Vitalii and
               Tapus, Nicolae},
  title     = {Ratio1 meta-{OS} -- decentralized {MLOps} and beyond},
  booktitle = {2025 25th International Conference on Control Systems and Computer Science (CSCS)},
  year      = {2025},
  pages     = {258--265},
  address   = {Bucharest, Romania},
  month     = {May 27--30},
  doi       = {10.1109/CSCS66924.2025.00046},
  isbn      = {979-8-3315-7343-0},
  issn      = {2379-0482},
  publisher = {IEEE}
}

IEEE Xplore: https://ieeexplore.ieee.org/document/11181620

@misc{Damian2025arXiv,
  title         = {Ratio1 -- AI meta-OS},
  author        = {Damian, Andrei and Butusina, Petrica and De Franceschi, Alessandro and
                   Toderian, Vitalii and Grigoras, Marius and Bleotiu, Cristian},
  year          = {2025},
  month         = {September},
  eprint        = {2509.12223},
  archivePrefix = {arXiv},
  primaryClass  = {cs.OS},
  doi           = {10.48550/arXiv.2509.12223}
}

arXiv: https://arxiv.org/abs/2509.12223

Vision: Democratize artificial intelligence by making decentralized, privacy-preserving ML infrastructure accessible to everyone—from individual developers to enterprises and academic institutions.

Mission: Build a trustless, economically sustainable AI ecosystem where:

• Innovation is unconstrained by infrastructure costs
• Privacy and data sovereignty are fundamental rights
• Compute providers are fairly rewarded for contributions
• Barrier to entry for AI development approaches zero

Through Ratio1, we're establishing the foundation for the next generation of decentralized AI applications that prioritize accessibility, security, and environmental sustainability.