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What is iExec RLC?

iExec RLC is a pioneering decentralized computing platform that connects developers with distributed cloud infrastructure through a blockchain-powered marketplace. Founded in 2016 by Gilles Fedak and Haiwu He, two researchers with backgrounds in distributed systems and grid computing at INRIA and CNRS in France, iExec raised approximately $12 million in one of the earliest successful ICOs of April 2017, selling out in under three hours.

The project's name, RLC, stands for 'Runs on Lots of Computers,' reflecting its mission to democratize access to high-performance computing resources by aggregating idle capacity from data centers, enterprises, and individual providers worldwide. iExec is headquartered in Lyon, France, and operates as one of the most prominent European blockchain projects in the Web3 infrastructure category.

The platform launched its mainnet in May 2018 and has since evolved through multiple stack upgrades, including the introduction of its Proof-of-Contribution (PoCo) consensus protocol, which validates off-chain computations on-chain without requiring every node to replicate the work. A defining milestone came through iExec's strategic emphasis on confidential computing, integrating Intel SGX Trusted Execution Environments (TEEs) to enable privacy-preserving computation on sensitive data.

This technology underpins iExec's partnerships with major enterprises and institutions, including a notable collaboration with Alibaba Cloud announced in 2018, partnerships with IBM on blockchain-oriented computing initiatives, and membership in the Confidential Computing Consortium alongside Microsoft, Google, and Intel. iExec has also participated in European Union research projects and received grants from BPI France to advance decentralized cloud standards.

The current ecosystem centers around several flagship products: the iExec Marketplace for computing orders, the Data Protector toolkit for GDPR-compliant data monetization, Web3Mail for decentralized privacy-preserving messaging, and the iApp (iExec application) framework that lets developers deploy dockerized applications to the network. In recent years, iExec has aggressively pivoted toward DePIN (Decentralized Physical Infrastructure Networks) and AI narratives, positioning RLC as a foundational token for decentralized AI compute, where GPU providers can monetize hardware for training and inference workloads.

The team has launched the iExec Builder Program and Voucher initiative to onboard AI developers, and the protocol has integrated with tools like Hugging Face for confidential AI model deployment. While iExec has faced competition from newer entrants like Akash Network, Render, and io.net, it has maintained differentiation through its enterprise-grade confidential computing stack and compliance-ready tooling.

The RLC token itself trades on major exchanges including Binance, Kraken and KuCoin, and serves as the medium of exchange within the marketplace, where buyers pay RLC to access computing resources and workers earn RLC for providing them. Governance discussions, roadmap execution, and community engagement are coordinated through the iExec blog, Discord, and governance forum, with the team publishing quarterly progress reports.

Despite broader market volatility affecting mid-cap infrastructure tokens, iExec continues shipping updates, expanding its developer SDK, and cultivating partnerships that reinforce its position as one of the more mature decentralized cloud computing protocols in the industry.

Key Features of iExec RLC

• Decentralized Compute Marketplace: iExec operates a fully permissionless marketplace where buyers, application providers, dataset owners, and workers transact using RLC tokens. This eliminates reliance on centralized cloud giants like AWS or Azure while offering competitive pricing through open market dynamics.
• Confidential Computing with TEEs: Through native integration with Intel SGX Trusted Execution Environments, iExec enables computation on encrypted data without exposing it to workers or third parties. This makes the platform uniquely suited for sensitive workloads in healthcare, finance, and AI model training.
• Proof-of-Contribution Protocol: iExec's PoCo consensus mechanism validates off-chain computing results on-chain without requiring redundant execution across all nodes. This hybrid approach delivers cryptographic proof-of-execution while keeping the system scalable and cost-efficient.
• Data Protector Toolkit: iExec's Data Protector SDK allows developers and users to monetize or share datasets in a GDPR-compliant, encrypted manner. Data owners retain full control and can revoke access at any time, unlocking privacy-first applications such as Web3Mail.
• DePIN and AI Compute Focus: iExec has positioned itself at the intersection of DePIN and decentralized AI, enabling GPU providers to monetize idle hardware for AI training and inference. Its iApp framework and Hugging Face integration make deploying confidential AI models straightforward for Web3 developers.

iExec RLC Use Cases

• Decentralized AI Training: Machine learning engineers can rent distributed GPU power through iExec to train and fine-tune models without committing to long-term cloud contracts. Confidential computing ensures proprietary datasets and model weights remain encrypted during the entire process.
• Monetizing Idle Hardware: Data center operators and individual users with spare computing capacity can register as workers on the iExec network and earn RLC by completing compute tasks. This creates a passive income stream while contributing to decentralized infrastructure.
• Privacy-Preserving dApps: Web3 developers can build decentralized applications that process user data confidentially via TEEs, ideal for KYC, medical records, or financial analysis. Tools like Web3Mail demonstrate how iExec enables private communication without centralized servers.
• Enterprise Data Monetization: Businesses holding valuable proprietary datasets can tokenize access and sell it on the iExec marketplace without ever revealing the raw data. Buyers pay in RLC to run approved algorithms against the dataset in a sealed environment.
• Rendering and Scientific Compute: 3D artists, researchers, and scientific institutions can offload rendering tasks, simulations, and large parallel computations to iExec workers. This provides a cost-effective alternative to traditional render farms and HPC clusters for time-sensitive projects.

iExec RLC Tokenomics

Total Supply

RLC has a fixed maximum supply of 87,000,000 tokens, established at the 2017 token sale with no inflationary emissions beyond this cap. This hard cap provides predictable scarcity relative to utility-token competitors that rely on continuous issuance.

Circulating

The circulating supply represents the majority of the total 87 million RLC, with the remainder allocated to team, reserves, and ecosystem development under vesting schedules that have largely concluded.

Utility

RLC is the native medium of exchange on the iExec marketplace, used by buyers to pay for computing resources, datasets, and applications, and earned by workers providing compute power. It also supports staking for workers to signal commitment and participate in the Proof-of-Contribution protocol.

Emission

There is no ongoing mining or inflationary emission of RLC; the total supply was minted at genesis in 2017. Token velocity is driven by marketplace activity and ecosystem incentive programs rather than scheduled unlocks.

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