AI agents that could reshape solver infrastructure from a complex, time intensive process into a profitable, efficient operation accessible to anyone. Early testing demonstrates that AIxecutors are delivering substantial returns while compressing what traditionally required hours of manual blockchain operations into milliseconds of autonomous execution.

t3rn is developing intent based bridging powered by AI agents that could enable anyone to deploy Solver operations without deep technical expertise or constant monitoring. t3rn's AIxecutors don't just automate existing processes, they create entirely new opportunities for generating sustainable onchain revenue streams, fundamentally changing the economics of crosschain operations and making blockchain interoperability autonomous, profitable, and accessible to all.

Executive Snapshot from our early testing

Key Findings:

• Top AIxecutors were processing millions of transactions with consistent profitability.

• Success rates above 95% demonstrate the reliability of AI agent execution.

• Reduced operational overhead makes execution accessible to a broader range of participants.

• Early results suggest strong potential for scaling profitable operations.
  
  

What is an Executor in the t3rn Ecosystem?

When someone wants to move assets from one blockchain to another, say from Base to Arbitrum, they need a reliable intermediary to ensure their transaction completes successfully. That's where Executors come in.

Executors serve three critical functions:

1. Transaction Facilitation: They bid on and execute crosschain orders, ensuring assets move seamlessly between different blockchains.

2. Risk Management: They provide a guarantee mechanism, either successful execution or a full refund.

3. Network Security: They maintain the integrity and reliability of the t3rn protocol through decentralized participation.

This eliminates the anxiety and risk traditionally associated with bridging and crosschain transactions.

Why AIxecutors Beat Legacy Solvers

Executors vs. Solvers: the same job, different badge.

In many intent based bridges (Across, deBridge DLN, Synapse RFQ), the party that fulfills a user’s intent is called a Solver or Relayer. Functionally, it’s the same role as a t3rn Executor: post collateral, pick up an order, move funds, earn the spread. We keep the Executor label because t3rn’s contract enforces an execute or refund guarantee, but architecturally it maps with what other ecosystems call a solver. That’s why, in the next section, we benchmark AIxecutors against the largest solver markets in production today.

The bottom line is that among intent based bridges, Across and deBridge sit at the very top, Dune dashboards show ≈ $25 B and $4 B in lifetime volume respectively, way ahead of Synapse RFQ, Connext, Hyperlane, and others. All of these platforms require significant capital and technical infrastructure, which naturally limits competition. t3rn's AI approach removes those barriers for smaller participants.

AIxecutor Testnet Performance: 22 Apr – 21 Jun 2025

Looking at t3rn's six test AIxecutors, the numbers tell an interesting story. The most interesting find is that size doesn't guarantee better margins. The largest Executor moved 100 times more volume than smaller ones but only captured 1.5 basis points. The midsized Executors targeting less competitive routes consistently earned 3 to 7 basis points, proving that strategy beats capital size.

All AIxecutors maintained strong reliability, with every one completing at least 75% of their bids and two exceeding 90% success rates.

Methodology: Data pulled from t3rn’s telemetry indexer (commit c4b6d3).

Profit = rewards − gas; Margin = Profit ÷ Volume × 10 000 (basis points).

Success = Executed ÷ Bids.

How the AIxecutor works

At a high level, an AIxecutor is an autonomous agent that combines a standard Executor’s transaction execution engine with an AI-driven decision layer. This enables AIxecutors to dynamically adjust their behavior in real time, to maximize profitability, success rates, and capital efficiency.

The architecture typically includes four key components:

1. Order Listener & Intent Parser

   AIxecutors continuously monitor the t3rn network for new intents. When a new intent appears, the parser module classifies the transaction, estimates profitability, and scores the opportunity against current market conditions.

   
   

2. AI Execution Strategy Engine

   Instead of static config files, AIxecutors use lightweight AI models to optimize:

   • Which chains and assets to prioritize

   • How to balance risk/reward

   • What pricing to bid for a given intent

   • Which RPC endpoints and fallback paths to use (to avoid downtime)

   • When to rebalance liquidity across networks
     
     

3. Execution

   Once an intent is placed and bid accepted, the AIxecutor looks to perform the crosschain execution. The AI layer is additive - it enhances but does not replace the core execution code, ensuring compatibility and compliance with t3rn’s settlement guarantees.
   
   

4. Rebalancing & Self-Monitoring

   AIxecutors maintain their own liquidity pools across supported networks. It constantly monitors:

   • Pool balance per chain

   • Volatility/risk signals

   • RPC reliability

   • Order flow velocity

   When necessary, the AIxecutor can autonomously rebalance funds across networks to maintain optimal execution performance.

Conclusion

Our testing data demonstrates clear value. AIxecutors achieve high success rates while generating consistent profits across different scale levels. The combination of automated decision making, risk management, and operational efficiency creates a compelling case for adoption.

AIxecutors address a fundamental challenge, making crosschain execution both profitable and accessible. Early participants have the advantage of operating in a less competitive environment while the technology is still emerging. As these systems continue to improve and more participants join, the opportunities will evolve, but the foundation for profitable execution is already established.

Whether you're looking to deploy $5,000 or $100,000 the AIxecutor model offers a structured approach to crosschain execution that removes much of the traditional complexity while maintaining the profit potential. If you're interested in joining our AIxecutor Program or would like more information, the fastest way is by joining our Discord and reaching out to our team directly.

–

This case study is based on early testing data from the closed t3rn AIxecutor program. Past performance does not guarantee future results. All investment carries risk, and participants should conduct their own research and risk assessment before participating in Executor activities.