Upcoming Integrations

Reputation-based airdrops

Using existing onchain and social graph data, communities and protocols utilize OpenRank to surface highly ranked or reputable contributors or participants. These rankings are based on reputation graphs, making it effective and transparent for airdrop allocations

Discover valuable users and apps

Onchain transaction graphs originating from reputable users are used as inputs for OpenRank to compute highly ranked or valuable users and apps on a particular chain.

Retroactive Public Goods Funding

To allocate public goods funding according to the impact generated by applicant projects, Openrank compute can be used to rank most valuable apps (see above use-case). In addition, reputation graphs based on domain-reputation-weighted expert votes can also be computed to generate project rankings (see MetaMask SPD use-case).

Spam Filtering and Personalized Recommendations

Permissionless messaging protocols can use OpenRank to filter out spam and recommend reputable users, based on a variety of reputation graphs.

Dapp Stores and Explorers

Personalized recommendation of apps on decentralized apps store and block explorers. Social and onchain transaction-based graphs are used to sort apps based on a user’s network.

Personalized and Channel specific Feeds

Powering community and channel specific rankings and feeds. In addition, personalized 'For You' feeds based on direct engagement reputation graphs.

Rating system for crowdfunding protocols

Crowdfunding protocols can use a community-driven ranking system for filtering, sorting, and rating crowdfunding projects to safeguard users and creators navigating the platform.

Contribution ranking in OSS communities

Open Source Software contribution graphs and dependency graphs benefit from open verifiable reputation ranking to surface contributions for the OSS community. Graph-based algorithms are used to capture peer-to-peer signals in this context.