[Chaos Labs] - Lagrange Onboarding Assessment

This assessment aims to determine the viability of Lagrange as an AVS secured by etherfi by assessing their offerings, their potential to generate sustainable value for ether.fi stakeholders, and the overall risks and benefits associated with onboarding them as an AVS. The analysis follows the established AVS onboarding framework, evaluating Lagrange across three key pillars: Product, Sustainability, and Utility.

Introduction

Lagrange Labs is a protocol utilizing zero-knowledge proofs to unlock new types of data-intensive and cross-chain application. The project raised $13.2 million in seed funding, led by Peter Thiel’s Founders Fund, and has since introduced three products: the ZK Prover Network, ZK Coprocessor, and Lagrange State Committees. The team comprises engineers and researchers with experience from organizations such as Protocol Labs, ZKsync, Consensys, Mina Protocol, and Chainlink. Their collaboration with the Applied Cryptography Lab at Yale University supports the technical development of these offerings.

The protocol comprises three interconnected products, each addressing specific challenges:

1. ZK Prover Network The ZK Prover Network is a decentralized network of operators that generates zero-knowledge proofs for various applications, including rollups and dApps. It leverages EigenLayer restaking and a modular design with the goal to offer scalable, and cost-effective proof generation with high liveness guarantees. This network essentially functions as a marketplace for on-demand proving services, enabling diverse use cases.

2. ZK Coprocessor The ZK Coprocessor is an offchain network of specialized nodes that can execute intensive computations and generate ZK proofs based on the results. This technology allows decentralized applications to verifiably access computations without requiring trust between the initiated task and the offchain prover. By leveraging the ZK Prover Network—and indirectly EigenLayer restaking—this product aims to facilitate the development of more complex and data-intensive decentralized applications.

3. Lagrange State Committees Lagrange State Committees provide a secure and efficient method to prove the state of optimistic rollups on Ethereum. Acting as a “fast-mode” for bridges and messaging protocols, LSCs use a dynamic set of nodes secured by rehypothecated collateral restaked with EigenLayer. This setup allows LSCs to attest to the finality of rollup states without waiting for the standard challenge period, enabling more timely cross-chain applications. Lagrange State Committees have been integrated with several L2s including Base, Fraxtal, and Mantle have and have generated over 30,000 state proofs and finalized 2,000,000 blocks

Product

A well-functioning product that delivers on its promises & generates consistent rewards for stakers and node operators, ensures a healthy return on investment for ether.fi’s different stakeholders. Conversely, a flawed or underperforming AVS can lead to financial losses, operational inefficiencies, and reputational damage for ether.fi, potentially deterring users and undermining confidence in the platform.

Lagrange’s ZK Prover Network and ZK Coprocessor target one of the most relevant problem in the current blockchain space and offers a potential solution. Its modular architecture is designed to enable decentralized, scalable proof generation, this system claims to reduce the risk of bottlenecks and central points of failure associated with current proof generation. While partnerships with established rollup providers like AltLayer and Caldera, alongside planned integrations with zkSync, Polygon CDK, and Scroll, indicate a degree of market interest, the participation of major industry players like Coinbase, Kraken, and OKX is another positive signal. All three products are in production and have returned a first set of adoption metrics that signal potential for broader adoption: Since launching as an AVS on EigenLayer in June 2024, the Lagrange ZK Prover Network has generated over 9 million proofs, while the Lagrange ZK Coprocessor has processed over 9 million queries across 650K+ blocks. In the last month, Lagrange State Committees have produced approximately 55K State Proofs and processed 10 million Finalized Blocks for Optimism, Base, and Arbitrum. However, the assessment of its value-add must remain cautious until the product demonstrates sustained market adoption and differentiation over a longer period of time.

Node operators earn rewards based on the amount of work they complete, with work capacity determined by the amount of restaked ETH. Lagrange offers various worker configurations (Small, Medium, Large), each with different hardware requirements. While rewards are primarily tied to the amount of work completed rather than the size of the worker, operating a larger worker may grant access to a different pool of tasks and enable proofs to be completed more quickly and efficiently, potentially leading to higher overall rewards. This structure also discourages freeloading, as a Prover with a disproportionately large stake only receives corresponding rewards if they contribute a significant amount of computation to the network.

Lagrange does not utilize slashing, so capital staked to operators faces no slashing risk. Instead of slashing, the main risk becomes non-payment. Provers receive a reward when they generate a valid proof within the allotted time. A Prover that does not fulfill its proof generation obligations in time will be penalized through non-payment. Failure to meet deadlines or fulfill proof generation obligations results in non-payment, which could negatively impact operators who have already incurred resource and operational costs. Additionally, operators may face gas costs associated with proof submission and verification. While slashing is absent, these factors could still lead to profit losses for operators. The relationship between hardware configurations, performance (e.g., proofs generated per unit of time) and potential penalization needs to be better defined to fully understand the operational costs and risk for the Node Operators working with erthe.fi.

Lagrange’s ZK proof generation products show promise in addressing a crucial blockchain need, boasting a modular architecture and initial traction. To ensure continued soundness, ether.fi should monitor Lagrange’s revenue generation, usage patterns, cost optimization for operators, and sustained adoption within the competitive ZK landscape.

Sustainability

Strong AVS sustainability is crucial for ether.fi stakeholders because it directly impacts reward consistency and the overall health of the ecosystem. If an AVS like Lagrange cannot sustain itself financially, it may struggle to provide consistent rewards to stakers and node operators, potentially leading to decreased participation and a decline in the value of the ether.fi platform.

With Lagrange, revenue is primarily generated from applications and blockchains requiring scalable and reliable proof generation. While this model aligns with growing demand for scalability and interoperability in the space, its long-term success depends on several factors, including demand consistency and broader adoption of ZK technologies, which exposes the model to market risks. Inconsistent demand for proofs, reduced interest in ZK proofs or limited traction in rollup ecosystems could affect revenue stability and operator participation.

Currently, Lagrange adopts a dual revenue model through user fees and token emissions. However, more clarity is needed on fee structures, such as how fees are calculated, their amounts, and projected revenue. Market volatility and concentrated token holdings could also impact income predictability.

Lagrange’s current setup demonstrates potential with its dual revenue model and technically scalable architecture. Areas for improvement and future monitoring include providing detailed information on the fee structure and revenue projections as well as potential market performance of the reward token. Furthermore, mechanisms to buffer income fluctuations, such as dynamic reward adjustments or supplemental funding pools, are recommended. Regular assessment of operator economics will also be essential to ensure Lagrange’s long-term sustainability and its contribution to a healthy ether.fi ecosystem.

Utility

Integrating the products of an AVS into ether.fi’s infrastructure can facilitate the early bootstrapping and growth of AVSs while enabling them to return value by performing essential services for the protocol.

To date, ether.fi is actively building with the Lagrange ZK Coprocessor to power the cashback feature for its crypto-native credit card, ether.fi Cash. This integration demonstrates Lagrange’s capability to perform verifiable off-chain computations, allowing ether.fi to calculate and distribute cashback rewards in a trustless and efficient manner. This highlights a strong synergy between the platforms.

Lagrange’s decentralized architecture is a critical factor in enabling such collaborations, as decentralization is a key criterion for ether.fi. The modular design of Lagrange supports scalability and customization, allowing independent subnetworks to address specific needs. By avoiding single points of failure and third-party dependencies, Lagrange’s architecture enhances resilience and aligns with ether.fi’s ecosystem requirements.

Lagrange demonstrates immediate utility through its operational integration with ether.fi Cash, where the ZK Coprocessor powers the cashback rewards program. This represents a clear and successful use case. Additionally, Lagrange’s architecture aligns well with the onboarding framework’s focus on decentralization, modularity, and security, providing a solid foundation for further integration.

Conclusion

Based on the assessment across the three pillars of Product, Sustainability, and Utility, Lagrange emerges as a promising AVS candidate for ether.fi. Its modular, decentralized ZK solutions address critical industry challenges—such as scalable proof generation and secure cross-chain state verification—and have already demonstrated notable traction through existing integrations (e.g., ether.fi Cash).

Despite these positive indicators, areas requiring greater transparency remain. A detailed breakdown of Lagrange’s revenue model, fee structures, and client usage—along with clearer guidance on operator hardware requirements and risk considerations—would bolster confidence in the network’s long-term viability. An articulated plan to manage income fluctuations, coupled with regular assessments of operator economics, will further solidify its sustainability.

At Chaos Labs, we endorse moving forward with the onboarding of Lagrange given its strong alignment with ether.fi’s AVS onboarding framework.

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