Legacy Approaches and Limitations
Last updated
Last updated
Over the past few years, we've seen many attempts to solve the problem of reputation in the decentralized world. Projects like Civic, Bloom, Cred and RociFi have all brought something to the table, offering new ways to think about identity and trust on-chain. But despite their innovations, none have truly cracked the code.
Most of these systems run into a few common issues that have held them back from broader adoption and effectiveness.
Centralized InfrastructureSome projects have relied on permissioned architectures or closed systems. That means while they may operate in the Web3 space, the foundations are still very much Web2; centralized databases, opaque APIs and limited user control. This creates a trust gap. If users don’t own or understand the infrastructure behind a system, it’s hard to trust the output it gives them.
Limited User AdoptionBuilding a great system is one thing. Getting people to actually use it is another. Many of the earlier identity and reputation tools had clunky onboarding, limited incentives for users or didn't plug into protocols where users were already active. As a result, adoption has been low and the data collected is too sparse to generate meaningful insights.
Isolated or Incomplete DataEven when data is collected, it’s often siloed; limited to specific platforms, chains or wallet types. A system might only track lending behavior on Ethereum, for example and completely miss relevant activity on Arbitrum or Solana. Without a complete picture, any reputation score is only telling part of the story.
TL;DRLegacy systems laid the groundwork, but they’re held back by:
Relying on centralized components.
Poor user experience and incentive design.
Narrow or non-composable datasets.
To build a truly Web3-native reputation system, we need something more flexible, decentralized and behaviorally intelligent; something that puts users first.
