No. AlgoLift is a no-code platform: you build strategies by wiring nodes on a visual canvas — indicators, logic, and order rules — and the AI copilot can build or edit them from a plain-English description. There's nothing to install and no scripting language to learn.

You compose strategies from nodes on a canvas: data, 38 indicators, price-action detectors (fair-value gaps, swing points, regression channels), logic and math, and order-management nodes. Real-time validation flags wiring errors before you run, and a Cmd-K quick-insert menu keeps the catalog a keystroke away.

The copilot builds and edits strategies from plain-English requests, proposing atomic graph changes that pass the same validator the UI uses before you ever see them. It also reads your results — and it will not praise an unvalidated backtest, instead naming the cheapest experiment to find out if your edge is real.

Tick-level history with market-by-order (MBO) order-book depth. ES and NQ go back to 2017, several equities to 2018, and a 2025+ set includes micros like MES and crypto. This is the same data the backtest engine replays print-by-print.

With Simulate Fills in Realistic mode, market orders walk up to 10 levels of historical order-book depth, limit orders model queue position, and latency delays every fill. Because the engine replays every tick, it knows whether the stop or the target hit first when both share a bar — it doesn't guess.

About 2–4 minutes for 10 years of tick-level data. Backtests split into monthly jobs that run in parallel across the cloud engine; strategies holding positions across month boundaries fall back to sequential execution to keep the equity exact.

Three ways: walk-forward optimization tests parameters on unseen data, the Monte-Carlo robustness suite resamples your results thousands of times, and trust surfaces like PBO and deflated Sharpe grade the optimizer's own honesty. The copilot won't call an in-sample result an edge until it survives that.

Any firm's evaluation. Topstep (50K/100K/150K) and Apex (50K/100K) ship as presets modeled on their published rules, and any other firm can be entered as fully custom rules. Presets are modeled on publicly available rules and can change, so verify current terms with your firm.

No. It's an estimate from resampling your strategy's trade distribution across thousands of evaluations — not a promise. We also track whether our predictions hold up against real outcomes over time, so a stated 60% is meant to mean 60%.

No. AlgoLift is not a prop firm and is not affiliated with, endorsed by, or sponsored by any. We're the test bench you use before and during an evaluation — to know your odds, find what's failing you, and fix it.

Plans are Starter $49, Pro $99, and Quant $199 per month, with two months free on annual billing. Every plan includes the full platform; plans differ in monthly backtest credits and copilot messages. See the pricing page for the details.

Backtest credits meter how much history you test. A run consumes credits based on the span of data it covers, so a quick idea check costs little and a decade-long tick-level backtest costs more. Each plan includes a monthly allotment and you can top up anytime.

Yes — you start with 100 backtest credits and no credit card. If you upgrade later, you keep everything you built during the trial. Paid plans are month-to-month and you can cancel anytime.

Yes. Your strategies, backtests, and results are private to your account, and we never sell or share them. Backtesting doesn't require your brokerage credentials, and strategy execution runs in isolated environments.

Forward testing runs your deployed strategy on new data each day and reconciles it against the Monte-Carlo bands you saw before deploying. Automated live execution is rolling out through supported broker connections; where it isn't available, you place the signals yourself. AlgoLift never trades without your setup and consent.

Every plan includes email support plus the full Guide and the community Discord, and Pro and Quant plans get priority support. You can reach us anytime from the contact page.