inco

The modular

confidential computing network

Inco is the universal confidentiality layer of web3, powered by FHE and secured by Ethereum, enabling the development of next frontier decentralized applications (dApps), providing confidentiality to existing blockchains, and breaking down the final barrier to Web3 adoption at scale.

Unlocking the next frontier of Web3

Encrypted state on-chain

Directly store encrypted data on-chain. No need for off-chain storage or coordination.

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Composable encrypted state

Perform state transitions on top encrypted data, fully on-chain. You can add, divide, and compare hidden values without having to decrypt!

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On-chain randomness

Generate random numbers on-chain for your applications. No need for external randomness services and directly build fun applications on-chain.

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Backed by the best
tools

Powered by Fully Homomorphic Encryption (FHE)

Often called the holy grail of cryptography, fully homomorphic encryption is a novel type of cryptography that enables computation on top of encrypted data without decryption.

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tools

Familiar smart contract

language and tools

Inco is fully compatible with Metamask, Hardhat, Remix, and more. Build your DApps in Solidity with the same tools used to build with Ethereum.

Only possible with

on-chain confidentiality

On-chain confidentiality is necessary for enabling Web2-like applications going beyond privacy use cases. It enables crucial game mechanics, is necessary for institutional adoption, and allows for practical tools to exist within the blockchain ecosystem.

Gaming & NFTs

Build novel types of crypto games such as gambling, bluffing, resource concealment, spying on players, sabotage, secret alliances, the fog of war, and more.

// Battleship.sol
euint8[4][4] public player1Board; 
euint8[4][4] public player2Board;

// 0: empty, 1: ship, 2: already attacked
function attack(uint8 _x, uint8 _y) public onlyPlayers { 
    uint8 target = TFHE.decrypt(targetBoard[_x][_y]);
    if (target == 0) {
        //...
    } else if (target == 1) {
        //...
    }
}
pattern 1
confidential compute layer

The confidential compute layer for blockchains

Build your DApp on any network. Our Confidentiality-as-a-Service (CaaS) enables customizable confidential state, computation and randomness to transparent blockchains such as Ethereum, Arbitrum, Base, Polygon, Optimism, and others.

Latest News

ETH Denver Recap

ETH Denver Recap

Mar 18, 2024

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Introducing: The Inco Gentry Testnet

Introducing: The Inco Gentry Testnet

Mar 01, 2024

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Confidentiality in the Rockies: Meet Inco @ETH Denver
Community

Confidentiality in the Rockies: Meet Inco @ETH Denver

Feb 23, 2024

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Inco Raises $4.5 Million to Build the Universal Confidentiality Layer
News

Inco Raises $4.5 Million to Build the Universal Confidentiality Layer

Feb 22, 2024

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Introducing Inco: The Modular Confidential Computing Network
News

Introducing Inco: The Modular Confidential Computing Network

Feb 22, 2024

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Stay up to date

Latest developments from Inco.

Community

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Feb

26

🇺🇸 Denver, USA

d/infra
Feb

26

🇺🇸 Denver, USA

Jessy Hacker House x Inco
Feb

23

🇺🇸 Philadelphia, USA

Penn Blockchain Conference
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FAQ

While it is true that FHE requires intensive computation and cannot support use cases that require scale (such as training ML models on top of encrypted data), it is currently fast enough to support crypto use cases. This is because not all the operations within a smart contract are confidential, and the waiting period for producing new blocks provides enough time for the computation needed.

Trusted execution environments (TEEs), and zero knowledge proofs (ZK).

  • TEEs

    • Blockchain systems built upon Trusted Execution Environments (TEEs) employ an approach where encrypted data is stored on the blockchain itself. The process involves decrypting the data within secure enclaves, such as Intel SGX, which securely house the decryption keys. However, it's crucial to acknowledge that these secure enclaves are not immune to potential vulnerabilities, notably those stemming from side-channel attacks that could compromise their integrity and security.

  • ZK

    • Zero-Knowledge Proofs (ZKPs) enable the verification of accurate computations without revealing the underlying confidential data. However, a limitation arises from the requirement that sensitive input data must be in its original plaintext form and stored externally. As a consequence, the concept of composability is hindered, limiting ZKPs to applications involving a single participant. This constraint narrows the scope of their utility to scenarios where privacy is essential but participation remains singular and non-collaborative.

We expect our initial mainnet to handle 10 TPS with a blocktime of around 8 seconds with CPU, and if needed, we can transition to GPU and scale to 20-50 TPS. However, we expect that FPGA hardware acceleration in 2025 will allow us to scale to 100-1000 TPS.

Our TFHE scheme is based on lattice cryptography, which has been endorsed by the National Institute for Standards and Technology (NIST) to be resistant to quantum computers.