EvercashOpen AppThis is no longer a build log. It is an operating project.
We have built the system, put it through live conditions, and learned what survives outside a spreadsheet. The work now is operational: finding the right opportunities, taking only the trades that make sense, and making the whole loop more reliable over time.
Five phases, from first route to a real operation.
The first working system
We moved from market research to a working arbitrage operation: live price collection, route discovery, transaction simulation, and a strict profitability check before anything could be submitted.
Execution became the product
The project reached its first live execution phase on Arbitrum. We stopped measuring success by opportunities found and started measuring complete routes, confirmed outcomes, failed attempts, and net results.
The operating loop closed
Monitoring, simulation, sizing, submission, and post-trade review became one continuous system. Every result fed back into route selection, gas limits, liquidity filters, and risk controls.
A wider opportunity surface
We expanded the set of pools and routes under observation, prioritized less crowded liquidity, and improved the system's ability to ignore attractive-looking spreads that could not survive real execution costs.
The main Evercash project
Today the arbitrage project is an operating system around roughly $1M in annual MEV opportunity. The focus is no longer proving that arbitrage works. It is improving consistency, selectivity, and the quality of every decision made before execution.
Progress measured in operating capability, not noise.
Live, not theoretical
The system has moved beyond dashboards and paper opportunities into monitored, executed routes.
Around $1M in annual opportunity
Our current opportunity surface is roughly a million dollars of MEV per year, before competition and execution costs.
Execution-aware decisions
Routes are evaluated after liquidity, fees, gas, slippage, and failure risk, not from headline prices.
Arbitrum-first operation
Lower execution costs and active liquidity made Arbitrum the first environment where the system found durable economics.
A repeatable operating loop
Detection, simulation, execution, and review now work as one disciplined process.
Built for selectivity
The strongest achievement is learning to reject more opportunities than we take.
Make the operation sharper, broader, and harder to displace.
Our next phase is not about adding features for the sake of a bigger surface area. It is about improving the quality of the decisions that already matter.
- 01Increase the share of detected opportunities that survive simulation and settle successfully.
- 02Extend coverage across more chains, pools, and execution venues without lowering risk standards.
- 03Improve private order flow, transaction placement, and latency so the system competes on execution quality.
- 04Make sizing and capital allocation more adaptive to liquidity, volatility, and current competition.
- 05Turn post-trade data into clearer operating decisions, with better attribution for every cost and failure.
- 06Build the most reliable small-team arbitrage operation we can: quiet infrastructure, disciplined risk, and measurable results.
We are not trying to look busy. We are trying to be right more often.
Every successful route is useful. Every rejected route is useful too, if we understand why it failed. That is the standard for this project: a system that gets more selective, more reliable, and more valuable with every cycle.