The platform

One engine. Every asset class.

A shared engine — brokers, market-data feeds, a backtester and a paper-trading loop — with the equities / Alpaca vertical live today and crypto, FX and prediction markets on the roadmap. Every vertical inherits the same backtest → validate → paper-trade → report workflow.

Start free→See Hedge Funds
Works with
LHV logoAlpaca logoInteractive Brokers logoSaxo Bank logomoomoo logo
The desk

One system. Ticker to track record.

Your AI trading squad spans five workflow stages — talk to any one directly, or let the orchestrator run the whole loop.

◧
Research & Signals
Screen the market, pull news, analyst ratings and fundamentals before you commit capital.
research:
◆
Backtest & Optimize
Sweep parameter grids or run a deterministic, reproducible study on real Alpaca data.
backtest:
◉
Paper Trade
Send the winning strategy live on Alpaca paper — background polling, PDT-aware.
trade:
◐
Validate & Reconcile
Cross-check every fill against market data and tie the DB out against the broker.
validate:
◼
P&L & Reporting
See what worked — P&L, top strategies, drawdown and per-run detail on demand.
report:
How it works?

You set the rules. AI helps you tune them.

01
Describe a strategy
Start from Buy-the-Dip, VIX, Momentum, Box-Wedge or any leaderboard skill, and pick your universe. Every rule is written down: entry, exit, size and risk.
02
Fine-tune the parameters with AI
Chat with the desk: the AI proposes dip thresholds, stops, targets and hold times, sweeps the grid on real Alpaca data and explains what moved the result and why.
03
Walk-forward, then go live
Re-test the chosen settings on unseen data, paper-trade them, then run them live in a cash-only sleeve of your own account, with every fill validated and the P&L reported.

Systematic trading, in short

Trading by fixed rules instead of in-the-moment judgment. Entries, exits, position size and risk limits are set in advance and applied the same way every time, so the same signal gives the same decision whether you are confident, scared or away from the screen. It is rule-based; algorithmic is just the delivery, the rules coded so a computer places the orders (many early systems were run by hand).

Signal
When to enter and exit.
Sizing
How much to trade each time.
Risk
Stops, exposure caps, limits.
Execution
How orders reach the market.

Unlike discretionary trading, a system is backtested on history first and only then traded live. Common styles: trend following, mean reversion, carry, statistical arbitrage and volatility strategies.

Origins: from rice charts to Medallion
  1. 1730Dojima rice exchange, Osaka: the roots of candlestick charting.
  2. 1900Bachelier models prices as a random walk.
  3. 1952Markowitz turns diversification into mathematics.
  4. 1969Thorp's Princeton Newport runs quantitative arbitrage.
  5. 1970sAfter 1971, trend-following CTAs (Campbell, Millburn, later AHL, Winton, Aspect); Bridgewater founded 1975.
  6. 1980sRenaissance (1982); the Turtles learn rules, not instinct (1983–84); Tartaglia's stat-arb desk at Morgan Stanley; D.E. Shaw.
  7. TodaySmart beta and high-frequency trading bring rules to every corner of the market.

The through-line: explicit, testable rules beat in-the-moment judgment.

Get started

Backtest it. Paper-trade it. Prove it.

Create an account and put the squad to work — bring your own Alpaca keys.

Start free→Continue with Google