Sorella Labs is a startup focused on addressing the issue of Maximum Extractable Value (MEV) within the Ethereum network, co-founded by Karthik Srinivasan and Ludwig Thouvenin. The two founders met at the University of Chicago and decided to start a venture due to their strong interest in blockchain technology. Srinivasan previously interned at Citadel, while Thouvenin gained internship experience at companies like Ubisoft. The company recently announced the completion of a $7.5 million seed funding round, led by Paradigm, with other investors including Uniswap Ventures, Bankless Ventures, and Robot Ventures. As the DeFi market continues to grow, the MEV issue has become increasingly prominent, and Sorella Labs’ innovative tools have been developed to tackle this challenge.

Background of the MEV Issue

MEV refers to the extra profit that miners or validators can extract by manipulating the ordering, insertion, or deletion of transactions. This phenomenon is particularly pronounced on the Ethereum network and poses various issues for users and the entire ecosystem.

Key Issues of MEV

User Losses
MEV activities often lead to user losses in transactions, particularly through malicious behaviors like sandwich attacks and frontrunning. For instance, in 2023, the Ethereum Foundation lost $9,101 in a transaction due to a sandwich attack by an MEV bot, while the attacker profited approximately $4,060. This situation exposes ordinary users to higher costs and risks when conducting transactions.

Market Inequity
The existence of MEV creates an uneven playing field, especially on DeFi platforms. Arbitrageurs and MEV searchers can profit by monitoring transactions in the public mempool, exploiting information asymmetry. This behavior undermines the competitiveness of regular users, placing them at a disadvantage in transactions.

Network Stability
While MEV provides additional income for miners and validators, overreliance on MEV may impact the network’s decentralization and stability. Miners may prioritize transactions that yield higher MEV profits, neglecting the needs of other users, which can lead to network congestion and delays.

Lack of Data Transparency
There is a lack of accurate statistics on the specific data regarding MEV on Ethereum. Although some studies indicate that realized MEV is only a lower bound, MEV can be generated at any time during user interactions with the blockchain, making it challenging to assess its total amount accurately. This complicates regulation and governance.
Statistics indicate that in 2023, approximately 26% of the revenue was obtained through MEV on Ethereum. This shows that validators’ primary income source still comes from block rewards rather than relying solely on MEV profits. There are already some solutions in the market to address the MEV issue, such as the Brontes and Angstrom tools launched by Sorella Labs. These tools aim to reduce malicious activities by increasing the transparency of the transaction ordering process.

Brontes Tool Overview

Brontes is an open-source blockchain analysis tool developed by Sorella Labs to address the Maximum Extractable Value (MEV) issue within the Ethereum network. This tool can process Ethereum block data, categorize transaction behaviors, and identify MEV through pattern matching and analysis. Here are the main features and characteristics of Brontes.

Brontes Dashboard（Source: Official website）

1. Transaction Data Classification
Brontes can classify transactions based on specific behaviors, including the initiator, recipient, transaction amount, and Gas fees. This classification capability allows users to gain a clearer understanding of different types of transactions and their impacts.

2. Structured Data Output
Brontes transforms raw Ethereum blockchain data into a structured, easily analyzable format, significantly simplifying the data preprocessing process. This feature is crucial for developers and researchers as it enhances the efficiency of data analysis.

3. Off-Chain Data Integration
Brontes integrates off-chain data (such as centralized exchange prices, metadata, and peer-to-peer data), making the analysis more comprehensive and accurate. This integration capability enables users to understand market dynamics from multiple dimensions.

Brontes provides a modular framework that allows users to create and apply different analytical methods based on their needs. Specifically:

1. Flexibility
Users can select different modules to handle specific data types, making the analysis more personalized and customized.

2. Efficiency
Enabling collaboration between modules allows complex analytical tasks to be broken down into simpler tasks, thereby improving overall efficiency.

3. MEV Identification and Prevention
Brontes identifies MEV activities through pattern matching and analysis, helping users understand potential risks. For example, it can detect losses caused by frontrunning or sandwich attacks, providing crucial reference information for liquidity providers and ordinary users.

4. Comparison with Other MEV Solutions like Flashbots
Compared to other MEV solutions like Flashbots, Brontes primarily focuses on application-level data analysis, while Flashbots emphasizes protocol-level optimization. Brontes enhances the quality of transaction execution by offering visual data analysis tools, allowing users to participate directly in addressing MEV issues.

Angstrom Tool Overview

Sorella Labs developed the Angstrom tool (not yet launched) and aims to reduce common arbitrage behaviors in decentralized exchanges, particularly on the Uniswap V4 platform. Here’s a detailed analysis of how Angstrom operates to mitigate arbitrage activities.

1. Auction Mechanism
Angstrom runs two auctions within each block. The first auction determines which transaction can be processed first, while the second auction is a bulk auction where all orders are executed at the same price. This mechanism aims to prevent frontrunning and sandwich attacks.

2. Transaction Ordering Optimization
In traditional transaction processing, miners typically determine the order of transactions based on Gas fees and submission times, making them vulnerable to frontrunners. Angstrom’s auction mechanism shifts the reliance from gas fees to bidding to determine transaction orders, thereby reducing the profit margins for malicious actors.

3. Preventing Arbitrage Activities
Angstrom’s design creates higher uncertainty for arbitrageurs when executing arbitrage operations. By implementing auctions within blocks, Angstrom effectively disrupts arbitrageurs’ plans, making it difficult for them to profit from price discrepancies.

4. Dynamic Price Estimation
Angstrom uses a dynamic time window to calculate the volume-weighted average price (VWAP) and estimate price differences between decentralized exchanges (DEX) and centralized exchanges (CEX). This calculation method forces arbitrageurs to confront more complex market conditions, thus lowering their chances of successful arbitrage.

5.Cost Calculation and Optimization
When identifying potential arbitrage opportunities, Angstrom considers cost factors such as Gas fees to ensure that users can accurately assess their real profit scenarios. This mechanism helps users better evaluate risks and rewards when conducting trades.
Angstrom’s innovation lies in its auction mechanism, which introduces fair bidding. This prevents frontrunners from easily gaining priority by simply raising Gas fees. Additionally, its bulk execution mechanism effectively avoids severe price fluctuations caused by large transactions, reducing arbitrage opportunities.

Sorella Labs Competitors

Flashbots
Innovation: Flashbots focuses on protocol-level MEV solutions by providing a transparent transaction ordering mechanism to reduce malicious behaviors.
Disadvantage: Its solutions are primarily concentrated at the core protocol layer, which may not directly meet the needs of application-layer users.

Eden Network
Innovation: Eden Network creates a dedicated transaction pool that allows users to prioritize their transactions, thereby reducing the impact of MEV.
Disadvantage: Eden’s mechanism relies on users paying additional fees, which may increase costs and be unsuitable for all users.

Arbitrum
Innovation: As a Layer 2 scaling solution, Arbitrum indirectly reduces MEV impact by lowering transaction fees and increasing processing speeds.
Disadvantage: While Arbitrum excels in scalability, its approach to addressing the MEV issue is not direct and still relies on other tools for a better user experience.

Sorella Labs addresses the MEV problem with Brontes and Angstrom: Brontes can monitor MEV activities in the Ethereum network in real time. By analyzing transaction data, Brontes helps users identify potential risks, optimizing trading strategies. Angstrom integrates with Uniswap V4 and utilizes an auction mechanism to determine transaction order, thereby preventing arbitrage behaviors. This innovation will help reduce user losses during the trading process.

Conclusion

Sorella Labs, with its innovative tools and strong market positioning, demonstrates significant potential in addressing the MEV issue within the Ethereum network. Despite facing intense competition and uncertainties related to regulation and technological risks, the company is expected to achieve greater success in the future through ongoing technological innovation and strategic partnerships, positively impacting the decentralized finance ecosystem.