Looking for rust Web3 blockchain project ideas? Our library of 48+ Web3 hackathon projects offers real-world implementations, code samples, and detailed case studies.
DeDe is a trustless scaling infrastructure for e-commerce & delivery platforms. Think of us as an L2 for deliveries like Amazon, DHL, FedEx, etc. We provide trustless deliveries while maintaining integrity and security.
A Dapp with a seamless UX to create and customize smart wallet without the necessity of knowing how to code a smart contract.
A decentralized platform empowering professionals to monetize their expertise.
Radyal brings cross-chain DeFi to the masses, by allowing users to farm advanced strategies from any chain, on anychain.
World's First Evidence-based On-chain Reputation Oracle. RepOracle allows smart contracts to access and use reputation data in real time, enhancing their functionality and reliability.
*INCOMPLETE* A backend notification system for apps using the SSPC contracts
KediTrees facilitates digital investments tied to real-world CO2 reduction in tree plantations, leveraging satellite data for accuracy. The platform ensures secure carbon credit trading and encourages sustainable investments, contributing to environmental preservation.
BlockBet: An innovative online casino platform integrating DeFi features, allowing users to provide liquidity with diverse tokens. Participants earn yield and potentially profit over time, supporting player activities in a decentralized, blockchain-powered gaming environment.
🚑 Streamlining distribution for disaster relief by putting it on-chain
Coincidence is a peer-to-peer matchmaking platform designed to connect individuals based on shared interests, passions, and collaborative projects. Everything is encrypted, private, and safe.
SquadFi let’s you easily bootstrap censorship-resistant, permissionless, and trustless multi-paw validator squads.
Themis is a framework for improving protocol incentives and optimizing for long-term loyalty through data-driven analysis. It delivers those improvements in a trustless manner using Zero-Knowledge Proofs over the Machine Learning model results (ZKML).