Clearing the Path to Chain Abstraction
Streamlining Liquidity Rebalancing Across the Modular Ecosystem
This chain abstraction series article was made possible thanks to our partners, Particle Network and Everclear, two projects at the forefront of improving the web3 experience for users.
Over the past few weeks, we’ve peeled back some of the layers making up the chain abstraction landscape, exploring both the Permission Layer—the interface users interact with to express a specific intent (outcome) using a unified balance—and the Solving Layer, which consists of off-chain sophisticated actors in charge of executing these user intents as efficiently as possible.
As a reminder, solvers will be the entities transacting on the blockchain on behalf of end-users, because remember, the goal of chain abstraction is to make the user experience indistinguishable from using a traditional web2 app. In other words, users shouldn’t even know they’re interacting with a blockchain in the first place.
In our previous article, we explained how solvers typically use their own liquidity to front users, resulting in faster execution times. Let’s revisit this with an example:
Alice expresses an intent to bridge 100 USDC from Polygon to Base.
A solver, Bob, competes for the right to fulfill Alice’s intent as efficiently as possible.
Bob fronts Alice 100 USDC on Base using his own funds that were already there (since Bob holds liquidity across multiple chains).
Alice now has her 100 USDC on Base, ready to use, but Bob’s 100 USDC is now stuck on Polygon. This gives rise to what’s known as the rebalancing problem.
The Rebalancing Problem
After fulfilling orders, solvers face the challenge of rebalancing their funds back to their operational chains. Currently, they rely on centralized exchanges (CEXs) and bridges to do this. However, as Everclear has found, about 80% of rebalancing activity could be netted, reducing the need for unnecessary transactions.
Looking at our example: Ideally, Bob would prefer to get his 100 USDC back on Base, as that’s where he expects more order flow (and revenue) to come in. However, in the current landscape, Bob would need to manually bridge those funds from Polygon to Base, incurring bridge fees and additional time delays. These operational costs eat into Bob’s profitability and could ultimately increase fees for the end-users.
That said, solvers compete on speed and cost: who can fulfill my intent as fast as possible, for the least amount of fees. Meaning a solver can only charge so much, because there will always be another, bigger firm or entity that can afford to pay those constant bridging fees (the amount of volume they take in would have to far offset this). Not only that, but the large firms may even have their own team (depending on volume) to manually handle this rebalancing of capital (to do the actual bridging).
Ultimately, this issue has led to a growing centralization of solvers, as only those with enough resources can afford to absorb the high costs associated with rebalancing.
To help combat this growing centralization, the chain abstraction stack needs a new component: a clearing layer.
The Role of a Clearing Layer
A clearing layer functions as a decentralized network that coordinates the netting and settlement of liquidity flows between chains. By handling the rebalancing of liquidity on behalf of solvers, dApps, market makers, and other participants, this clearing layer eliminates the need for manual rebalancing and reduces costs across the board.
Returning to our earlier example: Instead of Bob having to manually bridge his 100 USDC back to Base, the clearing layer would automatically net and settle liquidity for him. This would eliminate the need for costly and time-consuming manual processes.
In fact, this concept of “clearing”, isn’t something new. Clearing is prominent across the traditional web2 financial industry.
Payments: VISA
When Visa nets transactions, they’re essentially figuring out the final balances between all parties involved in the transactions (banks, merchants, and customers) over a certain time period (like a day). Instead of moving money for each individual transaction one by one, Visa batches these transactions and calculates the net amount that each party either owes or is owed.
Let’s look at an example:
Customer A (Alice) makes a $100 purchase from Merchant 1 using Visa.
Customer B (Bob) makes a $50 purchase from Merchant 2 using Visa.
Customer C (Charlie) makes a $75 purchase from Merchant 1 using Visa.
These are individual transactions, but instead of Visa settling each one separately, they combine them into a batch.
After a certain time period, Visa aggregates all the transactions that have occurred within that time.
Merchant 1 is owed $175 (because Customer A spent $100 and Customer C spent $75).
Merchant 2 is owed $50 (because Customer B spent $50).
Instead of moving $100 and $75 separately to Merchant 1 for Customers A and C, Visa just says, "Merchant 1 is owed $175 in total."
This process of combining the amounts and working with the net (total) amount is called netting.
After the netting process, Visa needs to settle the net amounts between the parties involved (the merchant gets the funds in their bank account).
Enter Everclear
Everclear is the first clearing layer in web3, allowing any solver, market maker, or intent protocol to plug into the network to leverage its clearing and rebalancing capabilities.
Although Everclear was unveiled earlier this year, the team behind it has been around for several years, as Everclear was previously known as Connext—a cross-chain bridging protocol that was the first to coin the term“Chain Abstraction”.
While Connext found success within its domain, they realized there was an under-explored yet critical area within the chain abstraction landscape—clearing. Fast forward to June 2024, and Connext rebranded as Everclear, the first web3 clearing layer.
Everclear’s clearing layer directly addresses the cost and complexity of rebalancing liquidity for solvers, an issue we outlined earlier. By coordinating the netting, rebalancing, and settlement of liquidity flows across chains, Everclear significantly lowers the operational costs by up to 10x, according to the team, making solving more economically viable and accessible to a broader range of participants.
Looking back at our original example, this would mean solvers like Bob in our earlier example would no longer need to manually bridge funds back to their preferred chain. Instead, Everclear handles this process automatically for Bob and the rest of the solvers leveraging the clearing layer.
In short, Everclear takes care of the following:
Netting: Netting means aggregating and offsetting multiple transactions to minimize the actual movement of funds. For example, if $100 is going from Chain A to Chain B, and $80 is going from Chain B to Chain A, only $20 needs to be moved from Chain A to Chain B after netting.
Rebalancing & Settlement: Ideally, a solver's balance should be continuously adjusted across chains. When a solver's funds are utilized from one chain to execute an intent on another, it is essential to restore their initial balance by rebalancing and settling any outstanding amounts between the chains involved.
How Does Everclear Work
Everclear operates using a Hub-and-Spoke model, where individual blockchain networks (like Ethereum, Arbitrum, or Optimism) serve as the "Spokes" and a centralized "Hub" functions as the core Clearing Chain (this would be Everclear’s rollup).
At the core of Everclear is its Intent Matching (Netting) mechanism, which is designed to reduce unnecessary transfers by pairing intents that can fulfill each other–this matching is done on the Hub.
Example:
As an example, let’s say Alice wants to send 100 USDC to Arbitrum, while Charlie wants to send 70 USDC from Arbitrum to Ethereum. Everclear's system would match these intents and "net" the transactions, so only 30 USDC needs to be moved from Ethereum to Arbitrum (100 - 70).
At the end of each epoch, Everclear finalizes the settlement, transferring tokens or updating balances across the respective blockchains. Essentially, Everclear settles the 30 USDC that actually needs to move between chains to reimburse the solver for the portion they fronted (the remaining 30 USDC)--Everclear processes the netted amount and adds 30 USDC back to the solver’s account on Ethereum.
Thus, the solver covers the immediate liquidity needed for Alice’s cross-chain transfer, and Everclear’s settlement layer handles the actual movement of funds to ensure the solver is reimbursed after netting the transactions.
By consolidating intents and automating liquidity rebalancing, Everclear minimizes the operational burden on solvers, allowing them to focus on identifying opportunities rather than manually managing liquidity pools.
Architecture:
In regards to Everclear’s rollup architecture:
Rollup Framework: Arbitrum Orbit
Rollup-as-a-Service (RaaS) Provider: Gelato
Messaging: Hyperlane AVS (via EigenLayer)--will rely on Hyperlane’s validator set until the AVS is fully live
Data Availability: EigenDA–will leverage Gelato’s Data Availability Committee (DAC) to start, but will be transitioning to EigenDA sometime
Everclear launched on mainnet last week, officially bringing. the first clearing layer to the market. If you’d like to learn more about the ins and outs of Everclear, you can read through their docs.
Wrapping Up
Now if we go back to the CAKE framework, we can see that settlement is the final step in the chain abstraction process.
The Permission Layer allows Alice to express cross-chain operations as intents, using one unified balance, giving her the same UX she’s traditionally used to in web2
The Solving Layer forms the backbone of these user intents. Solvers are the entities responsible for actually interacting with blockchains to fulfill Alice’s intent.
The Clearing & Settlement Layer makes the solving process more efficient, by managing rebalancing and settlement of capital between chains solvers operate on.
& yes, we added the clearing layer to Frontier’s CAKE Framework, resembling a similar setup as showcased by Everclear.
As mentioned several times throughout this chain abstraction series, chain abstraction is not one single product or protocol, but rather a culmination of various teams working across different layers of the stack to ensure users enjoy a seamless experience, similar to what they’re used to in web2-–the vision of a future where users interact with cool new blockchain dApps without even realizing they're on a blockchain.
& a huge thank you to our two additional partners who helped us craft this series: Arcana Network, and Nuffle Labs.