Wrote your strategy with AI? Make it safe to trade.
AI assistants like ChatGPT and Claude are a fast way to draft a trading idea — and we encourage it. But generated code that compiles and even backtests beautifully can still repaint, peek into future data, overfit to history or mishandle live orders, and those problems stay invisible until real money is on the line. We review, repair and validate AI-generated code for TradingView, MetaTrader, NinjaTrader, TradeStation and MultiCharts — the speed of AI, backed by more than twenty years of production trading-system engineering.
AI Code Audit
Fixed price · quoted by script size
Send us your AI-generated script. You receive a written report covering correctness issues, repainting and look-ahead bias, overfitting red flags, order- and error-handling gaps — and a clear recommendation: fix, rebuild, or safe to proceed.
A follow-on rescue starts where the audit left off — you pay for the repairs, not for finding the problems again.
Rescue & Hardening
Quoted after audit
We repair and productionize the script: correct the logic, add risk controls and proper session and timezone handling, make order management robust, and add logging and documentation — delivered as tested, deployable code.
Scope and quote come straight from the audit findings, so there are no surprises.
Strategy Validation
Fixed price · per strategy
An independent backtest with realistic costs, out-of-sample and walk-forward testing, and parameter-sensitivity checks — with a plain-English report of what the evidence does and does not support.
Useful before trading any system live, whoever wrote it.
We cover Pine Script, MQL4/MQL5, NinjaScript, EasyLanguage/OOEL, PowerLanguage and MultiCharts .NET (C#) — details on the platform pages.
What we check
The failure modes below are where AI-written trading code goes wrong most often — and what every audit examines.
Backtest integrity
Repainting, look-ahead bias, unrealistic fill assumptions and missing costs.
Logic correctness
Does the code implement your rules — including session boundaries, gaps, partial fills, weekends and DST?
Risk & order handling
Position sizing, stops, error handling, and disconnect and requote behavior.
Robustness
Parameter sensitivity, out-of-sample behavior and overfitting red flags.
Code quality
Performance, maintainability and platform best practices.
How it works
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Send the code
The script plus a short description of what it should do — any of our platforms, whichever AI wrote it.
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Receive the report
Plain English, within a defined number of business days: what is safe, what is broken, and what a fix costs.
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Decide freely
Fix it yourself with our findings, commission a rescue quoted straight from the report, or walk away better informed.
As with all our work, we improve engineering quality and provide honest evidence — we make no performance promises. Past results are not indicative of future performance; see the risk disclaimer.