Everclear - Exploring the First Clearing Layer with Partners

In this Twitter space hosted by Arbitrum which took place on August 20, 2024, Grag hosted Arjun, Sreeram, Jon, Tegan, and Luis to discuss the evolution and impact of Everclear, the first clearing layer, and its role in addressing fragmentation within the modular ecosystem, and how Everclear collaborates with partners like Hyperlane, The Graph, Eigenlayer, and Gelato Network to enhance cross-chain transactions and global liquidity, and more! Read our notes below to learn more.

Background

Garg (Host) – Contributor at Arbitrum

Arjun (Guest) – Co-Founder at Everclear

Jon (Guest) – Founder at Hyperlane

Sreeram (Guest) – Founder at Eigenlayer

Tegan (Guest) – CEO at The Graph

Luis (Guest) – Founder at Gelato Network

Everclear – an Ethereum layer 2 that facilitates settlement netting

Hyperlane – a permissionless interoperability layer

Eigenlayer – a protocol built on Ethereum that introduces restaking, a new primitive in crypto-economic security

The Graph – a web3 protocol for organizing and accessing blockchain data

Gelato Network – Software company enabling global companies to print locally, in a more efficient and eco-friendly fashion

Everclear’s Introduction and the Clearing Layer Concept: Insights from Arbitrum, Gelato, Eigenlayer, Hyperlane, and The Graph

Arjun mentions Everclear’s rebranding from Connext. He describes Everclear as the first clearing layer, a new primitive designed to address the critical problem of fragmentation within the modular ecosystem. Arjun indicates that he will elaborate on the Everclear thesis later in the discussion.
Jon mentions his seven-year experience in crypto. He explains that Hyperlane is building an open framework for interoperability, which has been instrumental in enabling Everclear. Their technology allows anyone to connect any chain on their own terms.
Sreeram talks about his project, which he started three years ago. He describes Eigenlayer as a mechanism for supplying crypto-economic security to general protocols. Sreeram expresses excitement about the new developments in building a uniform clearing house for the crypto space and mentions his long-standing relationship with Arjun.
Tegan from Edge and Node introduces herself as the CEO and explains their role in creating The Graph. She draws a parallel between The Graph and Google, stating that while Google organizes the world’s data for the web, The Graph does the same for Web3. Tegan highlights the importance of decentralized data access and integrity, explaining that The Graph allows developers and users to access data served by many different indexers, ensuring no single company controls the information.
Luis from Gelato provides a comprehensive overview of his company’s evolution. He explains that Gelato started as the first smart contract automation protocol four years ago and has since expanded into relaying and serverless Web3 function environments.
Luis highlights their recent launch of a roll-up as a service offering, which he describes as their current flagship product. This service allows projects to create their own blockspace and control its cost, potentially leveraging solutions like Eigenlayer DA to reduce expenses. Luis expresses enthusiasm for Everclear, describing it as a potential next step in the evolution of capital efficiency and lowering barriers to entry in crypto.
Luis mentions that he recently recorded a podcast with Arjun about Everclear, encouraging listeners to tune in for more detailed information about the project.

Everclear’s Vision for Seamless Cross-Chain Transactions: Addressing Blockchain Fragmentation and Enhancing Interoperability

Arjun explains that Everclear, formerly Connext, has been working since 2017 to make Ethereum and the Ethereum interchain usable for the average person. Their work led them from L2 scalability research to interoperability.
Arjun describes how Connext spent three years trying to solve the fragmentation problem in blockchain, aiming to allow users to use any application on any chain without needing to know which chain they’re on. They identified a core challenge: every project trying to solve this problem creates its own unique design, liquidity pools, and agents, which paradoxically worsens fragmentation.
Arjun introduces the concept of a shared communication layer for entities in the space, such as solvers, LPs, and market makers, to coordinate and facilitate cross-chain transactions more efficiently. Arjun draws a parallel with traditional finance’s concept of clearing, using Visa as an example to explain how transactions are aggregated, netted, and optimized behind the scenes.
Arjun reveals a key insight: 80% of the volume flowing between chains today is actually editable, meaning people are bridging about five times more than necessary.
Arjun outlines the Everclear vision: by coordinating backend liquidity providers, market makers, CEXes, and intent solvers, they aim to dramatically reduce the costs of moving liquidity between chains, making bridging seamless.
Arjun highlights how Everclear’s vision aligns with and builds upon the work of other projects like Hyperlane, The Graph, Arbitrum, Gelato, and Eigenlayer.
Tegan provides an example to illustrate the efficiency of Everclear’s approach: in a scenario where multiple parties owe each other money across different chains, Everclear’s clearing layer can eliminate the need for multiple transactions.
Tegan highlights the importance of this clearing layer being decentralized to prevent monopolies, censorship, and to promote freedom on the web.
Arjun acknowledges Tegan’s helpful example of how Everclear works.
Luis compares Everclear to Splitwise for bridging, which Arjun agrees is a great analogy. Arjun explains that Everclear, like Splitwise, records IOUs on a single system and figures out the final amounts owed.
Garg asks the guests to explain their projects’ roles in relation to Everclear.
Jon from Hyperlane explains that they provide the “connective pipes” or “plumbing” between different chains for Everclear. Hyperlane serves as the transport layer, enabling Everclear to expand to new chains independently.
Luis discusses the importance of Everclear for rollup-as-a-service providers. He explains the current dominant bridging model, which uses solvers and intent-based orders filled from their own liquidity.
Luis highlights the challenges of the current system, including capital inefficiency, limited token support, and slow rebalancing periods. He highlights that these issues become more pronounced in a world with hundreds or thousands of chains.
Luis describes Everclear as a solution to make the current model more feasible in a multi-rollup world by reducing the need for frequent rebalancing and coordinating among market makers and solvers.
Luis draws a parallel between Everclear and traditional financial systems like Visa, where competitors coordinate for mutual benefit. He explains how this coordination can reduce capital requirements and improve efficiency in cross-chain transactions.
Luis says that Everclear’s approach is necessary to scale from a few rollups to dozens or more, as it allows for better capital utilization across different chains.

Everclear and Eigenlayer: Enhancing Economic Security and Decentralization in Cross-Chain Bridging

Sreeram explains that Everclear uses an orbit rollup where claims are stated, which can utilize EigenDA instead of Ethereum DA. Within Ethereum L2s, Eigenlayer and restaking provide economic security for instantaneous claim passing.
Arjun highlights Eigenlayer’s importance in Everclear’s design, as it coordinates competitive market actors who may not trust each other. It provides necessary economic guarantees and allows for neutral, verifiable operations with attributable economic security.
Arjun gives an example: Everclear clearing $150 million in 30 minutes could be secured by $3 billion in Eigenlayer restaked security, providing clear, objective security measures.
Sreeram expands on economic security for bridges and clearing systems, outlining a crypto-economic equation where the system is secure if the transmitted value within the fraud proof period is less than the total economic stake promised for correctness.
Sreeram suggests potential advancements, such as redistribution mechanisms where slashed funds could be given to harmed parties instead of being burned.
Arjun stresses the increasing importance of this security model as Everclear scales to potentially thousands of chains, including traditional finance systems, requiring both credible security and consistent cross-chain operation.
Jon from Hyperlane addresses the “economic security is a meme” argument, comparing it to legal recourse in traditional systems and emphasizing its role as a deterrent to bad behavior.
Jon argues that in systems like Everclear using Eigenlayer, there are well-defined rules and consequences, with operators knowing exactly what they’ll lose for misbehavior.
Tegan highlights the commitment to building a decentralized internet, not rebuilding traditional finance. She acknowledges that current solutions aren’t perfect in terms of security, decentralization, and censorship resistance, but stresses the ongoing work towards these goals.
Arjun encourages projects to focus on solving specific problems rather than trying to address multiple issues. He highlights how Everclear collaborates with various partners, each solving a distinct aspect of the overall system.
Arjun discusses the concept of composability in the crypto space, noting that while it may seem lost due to modularization, it still exists at a lower level in the stack. This allows for the creation of innovative systems by combining different infrastructure pieces.
Luis asks Arjun to explain how Everclear brings the benefits of traditional clearing houses to cross-chain bridging without compromising decentralization or non-custodial guarantees.
Arjun provides a historical context of clearing houses, explaining their traditionally centralized and custodial nature. He clarifies that Everclear is a “clearing layer” rather than a clearing house, representing a fundamentally different approach.
Arjun explains that traditional clearing houses take custody of assets, whereas Everclear operates in a non-custodial, trust-minimized manner. It uses blockchain technology to create verifiable, decentralized systems that can interact with multiple chains.
Arjun describes how Everclear works by registering the state of interactions between parties on different chains. Users can indicate their desired outcomes, and Everclear computes the optimal way to execute these transactions across chains.
The system allows for flexible transaction parameters, such as timing and pricing preferences, and aims to net off transactions against each other for increased efficiency.
Arjun highlights that Everclear’s approach leverages the benefits of centralized computation (for efficiency) while maintaining the decentralized, trustless nature of blockchain technology.

Exploring Chain Abstraction and Liquidity Fragmentation in DeFi

Arjun explains Everclear’s process using an example of a market maker moving $1 million between chains, highlighting the use of Hyperlane for data bridging and Eigenlayer for security.
The Everclear system processes “invoices” (IOUs) in a queue, settling funds based on available balances and user preferences, allowing for efficient, low-fee transfers between chains.
Arjun introduces the concept of chain abstraction, where users don’t need to care what chain they’re on, though they can if they want to understand security implications.
Chain abstraction is gaining traction with many projects working towards this goal, with Arjun arguing that a clearing layer is necessary to achieve it without exacerbating liquidity fragmentation.
Luis views chain abstraction primarily as a solution for fragmented user experience rather than fragmentation itself.
Luis argues that developers, not end users, should make decisions about which chains to use, comparing it to how users don’t select specific AWS instances for streaming services.
Both Arjun and Luis emphasize that solving liquidity fragmentation is crucial for enabling chain abstraction, as funds need to be available across different chains for a seamless user experience.
Luis sees chain abstraction as more focused on UX and API layers, though he acknowledges that backend processes are necessary to support it.
Tegan expresses the importance of giving users the option to choose their preferred chain for security reasons, despite the potential impact on user experience.
Arjun discusses the challenge of achieving chain abstraction in a non-custodial way, balancing user knowledge and verification ability.
Arjun suggests the possibility of developing a system similar to SSL certificates for crypto-economically secure systems, allowing wallets to protect users and flag potential issues.
Sreeram highlights Eigen DA, a highly scalable data availability system now on mainnet, capable of 10 megabytes per second throughput, which is significantly higher than Ethereum’s 4844.
Luis announces that Gelato will soon enable Eigenlayer DA on their OneClick deploy product, allowing users to launch test nets as Arbitrum L2s, L3s, and Arbitrum chains on Base with EigenDA.
Arjun highlights the composability of these technologies, comparing it to NPM packages, and expresses excitement about the potential for infrastructure growth.
Arjun plugs the Graph’s upcoming Sunrise upgrade, which represents a full migration to their decentralized network.
Arjun praises Hyperlane for their permissionless interoperability and product quality, mentioning Everclear’s decision to work with them.
Arjun talks about Everclear’s plans to release more technical explanations and information about how their project fits into the broader chain abstraction thesis and involve migrating Connext’s legacy volume and transactions to the new system with some initial guardrails for safety.

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Show Information

Medium: Youtube (Video)
Show: Everclear (prev Connext)
Show Title: Everclear: Coordinating Global Liquidity – Exploring the First Clearing Layer with Partners
Show Date: August 20, 2024