From AI to Cross-Chain: #lagrange Three Major Modules Support the Trustworthy Foundation of Web3

How to solve the trust issues in the multi-chain era? What can we trust in AI inference results? @Lagrange Official has built a ‘trustworthy computing foundation’ with three major modules — Lagrange is not a single-point tool, but a Web3 infrastructure capable of handling cross-chain, AI, and data verification simultaneously.

First, let's look at the ZK Prover Network: with over 85 top nodes operating, computing power can be infinitely expanded, like adding a ‘super captcha’ to the blockchain, allowing for quick verification of even the most complex transaction data. The ZK Coprocessor acts as a ‘cross-chain translator,’ enabling low-cost retrieval and verification of both Arbitrum’s DeFi data and Polygon’s NFT status, so dApp developers no longer have to piece together a ‘multi-chain API puzzle.’ Most impressive is DeepProve, the world’s fastest zkML solution, which can provide a ‘mathematical stamp’ on AI inference results, enabling self-verification for medical AI diagnoses and financial AI risk control.

@Lagrange Official takes security to the next level: as the first AVS on EigenLayer, it directly uses Ethereum's re-staked assets for security endorsement, achieving both decentralization and trustworthiness. Not to mention the investment from capital giants like Founders Fund and Fenbushi Capital, the launch and airdrop by Binance have also given the LA token a solid scenario — staking LA can act as a node, and functionality calls cost $LA , making the ecology more vibrant and the token more valuable.

Now, whether it’s DeFi needing cross-chain reconciliation or AI projects needing to prove transparency, this set of modules #lagrange is indispensable. It proves that the ‘trustworthy’ in Web3 doesn’t rely on guesswork; code and mathematics are sufficient. The next step for #lagrange is likely to make ‘trustless computing’ an industry standard.