Broker-neutral AI trading

Manage your investments with an AI team.
In plain English.

Describe a strategy in a sentence. The AI builds and backtests it, deploys it to your own brokers, and watches risk around the clock. No code. No VPS. No quant degree.

  • Live markets connected
  • 30+ AI tools · evolutionary strategy engine
  • Stocks · Crypto · FX · prediction markets
Watch the running product in action — not a mockup.
Connects to the brokers you already use
  • Binance
  • Alpaca
  • Saxo Bank

01 · The problem

Retail trading tooling stopped a decade ago

The platforms traders pay for today were finished before modern AI existed — and it shows.

/01

Built before AI

Watch charts, click buttons, repeat. The workflow hasn't changed in ten years. Everything is manual.

/02

Nothing connects

Every market and broker lives in its own silo. One portfolio means five logins and zero overview.

/03

Automation means code

Going systematic still means scripting languages, VPS hosting, and broker plumbing — or paying someone who codes.

/04

Risk is an afterthought

No portfolio-wide limits. No kill-switch. No guardrails. The trader is the risk system.

What automation costs a non-coding trader today: charting ~$60/mo + VPS ~$30/mo + $100–1,500 to get one strategy coded. Every tweak is a new freelance order, days away. And still no unified risk control.

02 · How it works

One sentence. Three steps. Only what passes goes live.

The same prompt → validate → deploy loop that changed software engineering, now pointed at the markets — with a hard validation gate in the middle. Replace the whole stack with a single prompt.

  1. 01 · Describe

    Say what you want.

    Prompt your strategy in plain English. The AI assistant turns it into a structured, validated strategy — no code.

  2. 02 · Validate

    Prove it first.

    Backtest instantly on a walk-forward engine that mirrors live execution — profit factor, drawdown and a full equity curve, in seconds. It surfaces the losers before your money does.

  3. 03 · Deploy — only what passes

    Go live, safely.

    Push it to your own account — paper first, then real — inside hard risk limits and a global kill-switch. Agents monitor it 24/7.

“Build a momentum strategy on BTCUSDT 4h with an ATR stop, backtest it on the last 1000 bars, then paper-trade it.”

03 · The differentiator

Strategies that invent themselves

Don't have an edge yet? The genetic optimizer evolves brand-new strategies from your own market data — and proves them on data it has never seen.

/01

Evolutionary search

A genetic algorithm breeds and mutates thousands of indicator-and-rule combinations across generations, keeping what performs.

/02

You pick the objective

Optimize for return-over-drawdown, net profit, profit factor or total return. Whatever fits your risk appetite.

/03

Out-of-sample validation

Top candidates are re-scored on held-out data to expose overfitting. In-sample and OOS metrics sit side by side.

/04

Fully reproducible

Every run is seeded, so a winning strategy can be reproduced bar-for-bar. Research you can audit and trust.

Why it matters: the platform doesn't just run your idea — it can find one, then honestly tell you whether it survives on data it has never seen. That's the difference between a backtest and an edge.

04 · Long-term asset management

Also tools for long-term investors.

Looking to start with passive investing? Use our tools to build your portfolio and let AI optimize it over time.

Strategic asset allocation in the running app: Conservative, Balanced and Growth allocations kept on target, each with a plain-language rationale for every rebalancing trade.
Portfolio management — AI keeps Conservative, Balanced and Growth allocations on target. One click to rebalance, with a plain-language rationale for every trade.

Be early

Get on the list before launch

We're opening access in waves. Join now to claim early access, help shape the roadmap, and get the first invites when live deployment opens.

  • Priority invite when public beta opens
  • Free paper-trading & backtesting at launch

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