1. Introduction

The rapid growth of the Web3 ecosystem has to an increasingly diversified blockchain space. This reflects the maturation of the industry as user needs become more refined and technological innovation continues. However, this diversification also brings fragmentation. While diversity has benefits, the sharp rise in the number of chains raises concerns of over-complexity due to a complex multi-chain environment. DeFiLlama now lists over 300 registered chains. New projects are constantly announcing mainnet launches, further intensifying the market.

One of the biggest issues with multi-chain environments is the poor user experience. This arises from both the ecosystem’s complexity and liquidity fragmentation. Users encounter multiple challenges when transferring assets between chains. They must connect wallets for each chain, find the correct bridging service, and complete a complicated process of verifications and signatures. Additionally, they need to monitor assets across different wallets while managing gas fees and recognizing the network characteristics for each chain separately.

Liquidity fragmentation is another major concern. The Web3 industry combines the IT (Information Technology) layer with financial layers, so liquidity plays a critical role. Fragmented liquidity results in a poor trading experience and slows the growth of the industry. This issue became more apparent after 2021 as the number of chains in the Web3 space increased rapidly.

2. Leveling Up Cross-Chain Technology via Chain Abstraction

Cross-chain technology is gaining attention as a solution to the challenges posed by the complex multi-chain environment. It enables value exchange between different chains, which helps bridge fragmented liquidity and enhances the user experience.

However, this technology has limitations. Current cross-chain solutions primarily focus on direct connections between two chains, which does not fully address the complexities of a multi-chain environment. Specifically, the user experience when moving assets across multiple chains still requires improvement, and the unique characteristics of each chain continue to present challenges.

To address this limitation, the Everclear team introduced a groundbreaking technology in 2023 called Chain Abstraction. This technology advances cross-chain capabilities by abstracting the interaction between multiple chains from the user’s perspective. With Chain Abstraction, users manage assets from various chains as if they were in a single, unified wallet. This approach is expected to greatly enhance the user experience by eliminating the complexities and frustrations of multi-chain environments.

3. Chain Abstraction Is Not Magic

Chain Abstraction technology presents a surface-level simplicity, but it is built on a highly sophisticated technology stack. Similar to how we don’t consider the intricate workings of the internet while browsing the Web or how the engine works while driving a car, Chain Abstraction appears straightforward to the user. However, an intricate system operates seamlessly behind the scenes to deliver this ease of use.

Chain Abstraction technology is implemented through the Chain Abstraction Key Elements (CAKE) framework, which consists of three layers: 1) Permission Layer, 2) Solver Layer, and 3) Settlement Layer.

• Permission Layer: Connects user wallets and requests transactions across chains
• Solver Layer: Find and executes the optimal path for transaction based on gas fee and time
• Settlement Layer: Ensures transaction finality across chains.

The solver layer plays a crucial role. While asset movement and management are simplified for the user, the solver handles the complex task of finding and executing the optimized path based on the user’s intent. For instance, if a user wants to transfer assets from Arbitrum to Optimism, the solver first utilizes liquidity on Optimism to send the assets to the user. It then receives the assets from the user on Arbitrum.

4. Clearing: Enhancing the Efficiency of Chain Abstraction

Every technological innovation involves tradeoffs, and Chain Abstraction is no exception. While it significantly enhances the user experience, it shifts the operational burden to the solver and can lead to new challenges.

4.1. Challenges with the Solver Layer

The solver faces two main challenges. The first is the Liquidity Rebalancing problem, which occurs as the solver manages multi-chain asset movements on your behalf. Over time, the solver’s asset distribution shifts from the initial proportions and concentrates liquidity on certain chains. To correct this imbalance, the solver must periodically perform rebalancing operations. This process is time-consuming and costly, which results in an operational burden. It directly affects the solver’s efficiency and profitability and can ultimately impact the user experience.

Liquidity rebalancing is not just a problem for solvers; it’s an ecosystem-wide issue. Centralized exchanges (CEXs) must constantly rebalance due to asset outflows from user trades and withdrawals. Bridge services that frequently exchange funds, market makers, and large investors executing significant trades also face liquidity management challenges.

The second challenge is the centralization risk for solvers that stems from the liquidity rebalancing problem. Solvers with large asset reserves can manage liquidity rebalancing with relative ease. However, smaller solvers face time and cost constraints, which make rebalancing difficult. This could lead to market dominance by a few well-capitalized solvers and centralize the ecosystem. Such centralization increases network vulnerabilities and raises the risk of price distortions and market imbalances caused by the dominance of a few players.

4.2. The Clearing Layer: Drawing Inspiration from Traditional Finance

The issue of solver inefficiency can be addressed by adopting the concept of “clearing” from traditional finance. Clearing involves netting multiple transactions to reduce the actual movement of assets and improve efficiency. This approach is also widely applied in the payments industry.

Source: Everclear

A prime example is VISA. Processing hundreds of millions of transactions daily in real time would be inefficient in terms of speed and reliability. Instead, VISA aggregates transactions over a set period, nets them, and settles in batches. This approach saves cost, time, and reduces the strain on infrastructure.

Source: Everclear

The clearing concept is also expected to apply in a Web3 environment. According to Everclear’s analysis, about 80% of cross-chain daily transaction volume flows can be netted. This reduces the need for frequent asset movements and allows liquidity to be used more efficiently. Many transactions can be processed without actual asset transfers, greatly improving system-wide efficiency. This liquidity optimization is expected to effectively address the liquidity rebalancing challenges and centralization risks faced by solvers and the broader ecosystem.

5. Everclear: The First Clearing Layer

Everclear is the first layer in the Web3 industry to introduce the clearing concept. It nets transactions during cross-chain transfers to solve the liquidity rebalancing problem and enable more efficient liquidity management.

5.1. How Everclear Works

Everclear’s clearing mechanism operates using a Hub-and-Spoke model. In this setup, mainnets like Ethereum, Arbitrum, and Optimism serve as the spokes. Everclear acts as the hub, aggregating and netting their transactions.

Consider the following scenario: 1) User A sends 100 USDC from Arbitrum to Optimism, and 2) User B sends 100 USDC from Optimism to Arbitrum.

First, User A’s request is sent through an Intent queue from Arbitrum (the spoke) to Everclear (the hub). If no matching requests are available when it arrives at Everclear, the request is placed in the Invoice queue.

Next, User B’s request is sent from Optimism (the spoke) to Everclear (the hub). Since there are matching invoices in the queue, B’s request is added to the Deposit queue and matched once the conditions are met.

Once matched, Everclear sends a message to the Settlement queue for Arbitrum and Optimism. The message to Arbitrum instructs a transfer of 100 USDC from User A to User B, while the message to Optimism instructs a transfer of 100 USDC from User B to User A. This process facilitates a cross-chain transaction between the two users efficiently.

5.2. Beyond Clearing Innovation: Everclear’s Notable Technical Strengths

Everclear has focused its research and development efforts on solving the industry’s core challenges, resulting in technologies like Chain Abstraction and clearing layers. However, implementing such innovative concepts requires a strong technical foundation.

It’s essential to understand the technical strengths that support Everclear’s Clearing Layer. Below are three key strengths that we believe will play a crucial role in turning Everclear’s vision into reality and facilitating its adoption across the Web3 ecosystem.

Source: Connext

The first technical strength comes from Everclear’s extensive experience. The team has been running Connext since 2021 and has invested considerable effort in solving liquidity issues in a cross-chain environment. The xERC20 standard, which has gained wide adoption and positive reception within the Ethereum ecosystem, demonstrates the team’s technical expertise. This experience serves as a crucial foundation for the development of the clearing layer.

Source: Everclear

The second strength lies in ensuring high flexibility and scalability through modular design. Everclear uses a modular architecture instead of a monolithic one. By focusing on the development of clearing layer technology and employing a modular structure, Everclear makes it easier to integrate with other technologies. This approach allows each project to seamlessly incorporate Everclear into its existing infrastructure or adapt it according to its technical preferences. This design enhances Everclear’s broader applicability and increases compatibility with a wide range of projects.

Finally, Everclear efficiently handles large transactions. It is designed to optimize large transaction volumes by adopting a netting approach that reduces asset movement and lowers processing costs. The system uses a queue-based architecture to manage large transactions reliably. It also allows for adjustments in conditions such as queue size and processing intervals to suit specific situations. This flexibility makes Everclear a valuable option for cryptocurrency exchanges and market makers that deal with significant transaction volumes.

6. vbNEXT: Maximizing Efficiency with a New Token Model

While Everclear is expected to improve liquidity in the Web3 industry through its clearing layer, the cold start problem—securing liquidity in the early stages—remains a challenge for new projects. This lack of liquidity limits project growth and user acquisition, posing a significant barrier to innovation and competition. Early-stage projects often resort to incentivizing market makers or bridges to provide liquidity. However, this can be costly to many. To address this, Everclear plans to introduce a new token model called “vbNEXT” to solve the cold start problem for these projects. The model leverages the existing NEXT token ecosystem.

The core of the vbNEXT token model is to provide liquidity to underutilized chains or paths. Token holders stake NEXT tokens to acquire non-transferable vbNEXT tokens, which serve as voting rights for specific chains (spokes) during each Epoch.

Votes are counted through the Gauge System. After each Epoch, a weight is calculated based on the number of votes per gauge. This determines the distribution of NEXT tokens to each spoke, with solvers rewarded according to the volume of transactions they process. Chains with more votes receive a larger share and rewards. As more solvers join, individual earnings decrease, prompting solvers to migrate to less competitive chains.

This mechanism is expected to efficiently distribute liquidity across the ecosystem and offer a solution to the cold start problem faced by new projects.

7. Closing Thoughts

Everclear recently announced the launch of its mainnet beta. The clearing layer and vbNEXT token model are expected to bring positive changes to the industry and will become increasingly important as the multi-chain environment expands into L2 and L3. Various liquidity providers, such as solvers, exchanges, market makers, and bridge services, will be able to use their assets more efficiently and unlock new opportunities and services.

Currently, Everclear supports EVM-compatible chains, but it plans to expand support to include other environments such as SVM and MoveVM. This will enable Everclear to achieve greater scalability in a multi-chain ecosystem and make it more accessible to a wider range of users and developers.

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