Janction

Janction is building the foundational infrastructure for decentralized artificial intelligence by merging distributed computing with blockchain-backed coordination. The platform serves as a powerful AI compute marketplace, where users can securely rent, contribute, and manage GPU power for machine learning workloads across sectors like image generation, object detection, speech recognition, and LLM hosting. The system is designed around resource interoperability, verifiability, and economic fairness.

At its core, Janction employs a unique cluster GPU pool architecture to handle scalable parallel workloads. This system supports a wide range of devices—from RTX 4070s to H100s—allowing dynamic task scheduling, GPU allocation, and fault-tolerant load balancing. The platform uses containerization and orchestration frameworks like Kubernetes and Kademlia (K8s) to standardize and index distributed resources for seamless GPU management.

One of Janction’s defining innovations is its Proof of Contribution protocol—an incentive model that verifies and rewards honest participation by measuring actual computational workload. This ensures fair distribution of earnings for GPU providers and supports decentralized AI model training without the need for a centralized authority. The platform also integrates robust privacy and compliance features, including encryption keys, tamper detection, and localized processing to meet legal standards in regions like Japan.

The system architecture enables full-stack AI pipelines, from data acquisition and pre-processing to inference and model fine-tuning. Janction decouples data, compute, and models—allowing these components to interact via smart contracts, ensuring transparency and auditability. A built-in gaming mechanism regulates roles in the network (e.g., data providers, model builders, GPU hosts) through workload correlation functions and VCG pricing to optimize network performance and balance incentives.

Designed for AI developers, research labs, and enterprise clients, Janction offers APIs, SDKs, and microservices for easy model deployment and fine-tuning. Users can host private LLMs, process high-resolution videos, run real-time object detection, or automate AI-based content creation at scale. Unlike centralized AI clouds, Janction provides open access, verifiability, and composable infrastructure with true decentralization.

When compared to competitors like Akash Network, RunPod, or CoreWeave, Janction stands out by deeply integrating AI-specific primitives such as data labeling, verifiable compute, parallel training, and private LLM support—all coordinated on-chain.

Janction provides a comprehensive suite of features designed to make decentralized AI accessible, scalable, and economically viable:

• GPU Marketplace: Users can rent or lease GPU power from a distributed pool, with flexible pricing based on device specs and location. Transparent costs and real-time availability.
• Decentralized AI Cluster: Janction’s GPU pool system supports large-scale parallel computing, enabling AI model training and inference with optimized resource scheduling.
• Proof of Contribution: A fair contribution verification protocol ensures that rewards are distributed proportionally to actual work performed by GPU providers.
• Smart Contract Coordination: Key AI elements—models, data, GPUs—are coordinated on-chain to ensure transparency, traceability, and immutable execution.
• Flexible Pricing & Packages: From ¥3/min on RTX 4090s to H100 at $1.30/hr, Janction offers enterprise, standard, and business tiers with secure storage and regional compliance.
• AI Use Cases: Supports advanced AI tasks like image generation, speech-to-text, video enhancement, object detection, and LLM hosting.
• Privacy & Compliance: Full support for encrypted data processing, localized node deployment, and legal compliance (e.g., Japan region exclusives).
• Developer Ecosystem: Includes APIs, containerized runtimes, resource indexing, and workload routing algorithms for efficient deployment and system scalability.

Janction offers a user-friendly onboarding process that allows both individuals and enterprises to begin utilizing distributed GPU resources quickly:

• Step 1 – Create an Account: Visit Janction and sign up using your preferred method. Accounts can be created in under 5 minutes.
• Step 2 – Choose Your GPU Plan: Select from available devices like RTX 3090, H100, or 4080, with hourly pricing clearly listed. Users can filter based on location, VRAM, or compute needs.
• Step 3 – Connect to the Node: Janction provides multiple connection protocols. Use secure SSH, remote desktop, or browser-based terminals to interface with the GPU.
• Step 4 – Deploy Your Model or App: Upload your AI workload, choose runtime environments, or deploy containerized models using the Janction dashboard or CLI.
• Step 5 – Monitor & Optimize: Access multi-terminal resource monitoring, logs, and system metrics. Scale or pause workloads as needed through the user panel.
• Step 6 – Secure Your Data: Use encryption keys, tamper detection, and dedicated storage to safeguard data. Enterprise users can deploy nodes in exclusive regions for compliance.
• Step 7 – Join the Community: For technical support and developer updates, follow Janction on Twitter.