Solving the Cross-Chain Liquidity Rebalancing Problem with the Clearing Layer
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Everclear, formerly known as Connext, recently launched with a fresh focus as the Clearing Layer aiming to solve the ever-present modular fragmentation problem.
Today we talked with Arjun Bhuptani, about their history coining the term “chain abstraction”, building an intents-based bridge, and now working to collaborate with the intents and solver community. With Everclear, they are focusing on the clearing layer and chain abstraction stack.
We discussed the critical challenges of liquidity management for intent protocols and solvers and how to solve these by enabling solvers to net out their flows between chains, reducing the need for frequent rebalancing and lower interoperability costs. This approach not only makes it easier for solvers to operate across multiple chains but also addresses the centralization risks present in the solver landscape.
This centralization and single-solver dominance is something we’ve been thinking about at The Rollup so it was nice to hear Arjun’s POV on handling this situation.
Overall, we’ve seen the market for intent-based protocols and solvers expand dramatically, and Everclear’s clearing layer is designed to thrive in this landscape. But, can they do what they set out to and get the “buy-in” from the right players? We asked Arjun and he answered this, and the centralization question with ease.
The other big issue we brought up is the extensibility problem faced by many interoperability protocols, where they cannot scale to ‘infinite’ separate environments because of their infra constraints…we also asked Arjun how Everclear is able to scale as the number of chains grows. Lots of good tidbits.
Currently, the project is live on testnet, with plans to finalize their dutch auction system for pricing and netting. The team is targeting a full launch in Q3, incorporating ongoing developments and feedback.
Enjoy this somewhat technical dive into the landscape of cross-chain intents and interoperability.
The Rollup
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