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Platform
Fourteen surfaces across research, automation, data and community — all reading the same prices, the same indicators and the same calendar. Nothing gets re-entered when you move from a question to a screener to a live alert.
Each card links straight into the surface it describes. Narrow the grid by category, or read the whole thing top to bottom.
Fourteen surfaces, one data layer. Anything you find in one of them is one click from all the others.
These are not fourteen separate apps behind one login. A question becomes a screen, a screen becomes a backtest, and a backtest becomes something that keeps running without you.
Put the question to Quant in plain language. It reads the chart on screen, the volume profile and the calendar, then answers with the bars it used.
Turn that answer into a filter across 60,000 instruments. Save it as a preset and it keeps re-running as the session moves.
Send the preset to the backtester. Ten years of bars, modelled commission and slippage, and a trade ledger you can argue with.
Promote the surviving rule set to an alert or a hosted AlgoBeamTS worker, with the risk console holding the hard limits.
Every feature on this page is reachable from every account. What changes with the plan is how hard you can push each one — this is the floor and the top of the range, read straight out of the pricing matrix.
Live on Free. No card, no expiry date.
The limits that come off on the top plan.
Enterprise goes further again: twenty-five seats and up, twenty-five years of history, SSO with audit logs and a dedicated AlgoBeamTS worker pool.
See the full comparisonComposite feedback from our simulated community. Every name, desk and handle below is fictional.
I used to keep a spreadsheet of gap statistics that took an hour every Sunday to update. The screener preset does it in four seconds and the alert fires at 09:31 with the names already ranked by relative volume.
The walk-forward report killed a strategy I had been trading for eight months. In-sample it looked wonderful; out-of-sample the profit factor fell to 0.94. Painful, but that is exactly what I pay a research tool to tell me.
We moved our whole signal layer onto AlgoBeamTS. One script, run in the browser for the preview and on a worker for the live loop, and the two produce byte-identical output. That alone removed a class of bug we had chased for a year.
I ask Quant for the last six earnings reactions on a name before I size anything. It gives me the day-one moves, the drift after, and the volume profile, and it links each number back to the print it came from.
The risk console blocks orders that would push me over 2% correlated exposure. It has stopped me three times this quarter, and every one of those blocked baskets went on to have a rough week.
Market Replay is how I train juniors now. I put them on 12 March 2026, hide the future, and make them narrate the tape bar by bar. Two weeks of that beats two months of reading about volatility.
The heatmap grouped by sector with a five-day window is the first thing on my screen every morning. It tells me where money rotated overnight faster than any three dashboards I used to keep open.
I export every strategy to AlgoBeamScript and keep it in git next to the rest of my code. Reviewing a strategy change as a diff, with the backtest attached to the pull request, changed how disciplined I am about it.
What sold me was the honesty of the backtester. It charges commission and spread on every fill and shows the trades it could not have filled at all. My curves got uglier and my live results got much closer to them.
Ready when you are
The free plan never expires and never asks for a card. Open a chart, fork a strategy and run your first AlgoBeamScript backtest in about five minutes.