Automated MEV discovery & execution infrastructure: building low-latency systems for on-chain value extraction

Miner Extractable Value (MEV) is often described as an opportunity. In reality, it is an infrastructure problem.

The difference between profit and loss is not the idea. It is latency, execution guarantees, and adversarial awareness.

This project focused on designing a low-latency MEV research and execution system that could safely identify and act on opportunities while minimizing exposure to public Mempool risks and capital loss.

Why MEV is an infrastructure problem

Most discussions around MEV focus on strategies like Arbitrage, liquidations and sandwich attacks. But in practice, these strategies are commoditized. What actually matters is:

• How fast you detect an opportunity
• How safely you execute it
• How well you avoid adversarial interference
• How rare is your opportunity

The same strategy can be profitable or loss-making depending purely on execution quality.

Core challenges in real-world MEV systems

1. Extreme latency sensitivity

Opportunities exist within narrow time windows tied to block production intervals, mempool propagation delays, state changes across liquidity pools

Delays of even a few milliseconds can invalidate a trade.

2. High competitive pressure

The MEV ecosystem is dominated by specialized searchers, validators / block producers and players with co-located infrastructure. This creates an environment where:

Any detectable opportunity is already being targeted by multiple actors.

3. Execution risk in public mempools

Submitting transactions publicly exposes them to front-running, sandwich attacks. transaction reordering.

This often leads to failed execution, worse pricing, direct losses.

4. Capital safety constraints

Unlike theoretical models, real execution involves Gas costs, partial fills and state changes between simulation and execution

Without strict safeguards, losses compound quickly.

What we built

The system was designed as a modular MEV discovery and execution stack, combining off-chain intelligence with on-chain guarantees.

1. Opportunity detection engine

An off-chain engine continuously monitors blockchain state, liquidity pools across DEXs, and pending mempool transactions. It identifies opportunities such as cross-DEX arbitrage, price discrepancies, and event-triggered state changes.

The focus is on real-time signal generation, not batch analysis.

2. Atomic execution contracts

All strategies are executed through custom smart contracts designed for atomicity. These contracts bundle multi-step transactions into a single call, enforce conditional execution based on profitability checks, and revert entirely if conditions are not met.

If a trade is not profitable at execution time, it does not execute at all.

This eliminates partial loss scenarios.

3. Private transaction routing

Instead of broadcasting transactions to the public mempool, the system uses private relays and direct validator pathways where applicable. This reduces exposure to front-running, controls transaction visibility, and improves execution reliability.

4. Simulation and fork testing framework

Before deploying capital, strategies are validated in forked chain environments under realistic state conditions. This includes replaying mempool scenarios, estimating gas costs, and validating profitability across varying conditions.

Simulation is treated as a prerequisite, not an optional step.

5. Chain and strategy evaluation framework

Not all chains or strategies are worth pursuing. The system includes a structured evaluation layer that considers competition intensity, gas costs, liquidity depth, and execution reliability.

This helps avoid overcrowded strategies and environments with negative expected value.

Architecture overview

A. Data layer

• blockchain nodes
• RPC endpoints
• mempool listeners

B. Detection layer

• opportunity engine
• pricing and state analysis

C. Execution layer

• atomic smart contracts
• transaction builders

D. Routing layer

• private relays
• transaction submission

E. Simulation layer

• forked environments
• pre-trade validation

F. Analytics layer

• performance tracking
• strategy evaluation

Execution guarantees and failure handling

A critical part of the system is handling failure scenarios. The design ensures:

• Trades revert if slippage exceeds thresholds
• Execution aborts if gas costs exceed expected profit
• No state changes occur on failed opportunities

This is achieved through on-chain checks, pre-trade simulation and conservative execution thresholds

Lessons from real-world MEV environments

Building the system revealed several practical insights. Most apparent opportunities are already priced in, latency advantages compound more than strategy complexity, public mempool strategies operate in highly adversarial conditions, and mature chains offer fewer exploitable inefficiencies.

The bottleneck is not finding opportunities. It is executing them safely and consistently.

What this enables

With the infrastructure in place, the system supports:

A. Rapid experimentation

New strategies can be tested quickly within the same pipeline, reducing iteration time.

B. Capital protection

Atomic execution and rigorous simulation significantly reduce downside risk.

C. Cross-chain adaptability

The modular design allows seamless extension to new chains and environments.

D. Informed strategy selection

Resources are allocated only to strategies with positive expected value, improving overall efficiency.

Final thoughts

MEV is often framed as a strategy problem.

In reality, it is a systems problem involving latency, execution guarantees, and adversarial environments.

Without the right infrastructure, even the best strategies fail.

This project demonstrates that sustainable MEV participation requires not just ideas, but a carefully engineered execution stack that prioritizes speed, safety, and adaptability.

You can read complete case study here: https://www.zobyt.com/work/automated-mev-discovery-and-execution-infrastructure

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At Zobyt, we have built several systems like this to enable transparency and efficiency through technology . If you’re interested in something similar, do reach out to discuss@zobyt.com