Now in public beta

Turn your thesis into a
live trading algorithm

Describe what you believe. AI builds the algo, backtests it with real data, and trades it on Alpaca.

algothesis
>
Free — no credit card · 3 strategies per day
2,400+
Strategies generated
18,000+
Backtests run
142
Tickers analyzed

Inside the Strategy

How “Utility Monopolies” was built

Someone typed “everyone is buying ai stocks but ignoring the companies selling the electricity” — here's what the 3 AI agents did with it.

1

Your thesis became tickers

The Momentum Agent scanned 300+ large-cap stocks and identified power utilities as the strongest match — companies that literally sell electricity to AI data centers.

  • Mapped 'selling the electricity' → power generation sector
  • Filtered for AI data center exposure + strong momentum
  • Selected NEE, CEG, VST as top picks
Thesis → Positions

Everyone is buying AI stocks but ignoring the companies selling the electricity

LONGAI Power Infrastructure
NEElong35%+73.2%
CEGlong35%+89.4%
VSTlong30%+112.3%
2

Catalysts shaped the timing

The Catalyst Agent checked earnings dates, Fed meetings, insider trades, and analyst ratings. It found that NEE had beaten earnings 3 quarters straight — and the next report was 18 days out.

Events Detected
📊
NEE Earningshigh

In 18 days — beat last 3Q by avg 12%

🏢
CEG Insider Buyshigh

4 buys totaling $2.1M in last 30d

🏛️
Fed Meetingmedium

In 6 days — rate hold expected

📈
VST Analyst Upgrademedium

Goldman → Overweight, PT $95

3

Backtested on real data

The Risk Agent ran a full 1-year backtest. The result: +90.4% return with a 1.6 Sharpe ratio — beating buy-and-hold by +45.1%.

  • DCA + dip buying automated entry timing
  • Scale-outs at +25%, +50%, +100% locked in profits
  • 12% trailing stop limited max drawdown
1-Year Backtest ResultsPASSED
+90.4%
Strategy P&L
+45.1%
Alpha vs S&P
1.6
Sharpe Ratio
-14.2%
Max Drawdown
1yr backtest · Real price data · DCA + dip buy + scale-out + trailing stop

Another Example

Rate cuts are likely even with elevated inflation

A macro thesis about interest rates. The engine identified rate-sensitive assets across bonds, REITs, and growth stocks, then built three portfolio strategies with different risk profiles — all backtested against 12 months of data.

Purest Play
Duration Play
TLTlong40%+41.3%
SCHDlong35%+22.8%
SHYshort25%+3.1%
+24.9%S:1.3 · DD:-9.1%
HIGHEST BACKTEST RETURN
Highest Momentum
REIT Revival
Olong35%+33.4%
VNQlong35%+28.1%
DLRlong30%+45.2%
+35.1%S:1.5 · DD:-12.8%
Diversified
Growth Rebound
QQQlong40%+38.6%
ARKKlong30%+52.1%
XLUlong30%+15.3%
+36.2%S:1.2 · DD:-18.5%

Your turn

What do you believe
about the market?

Type your thesis. We'll turn it into a backtested trading algorithm.

Free account · 3 strategies per day · No credit card

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Community

What people are building

Real theses from beta users. Backtested with the same engine you just saw.

Top theses by alpha
1

Rising tariffs will shift manufacturing back to the US and boost domestic industrials

XLICAT
+41.2%
+28.5% alpha
2

Digital-first banks are outpacing traditional banks with younger demographics

SOFINUHOOD
+100.8%
+72.1% alpha
3

AI needs electricity more than chips right now

NEECEGVST
+90.4%
+45.1% alpha
4

Rate cuts are likely even with elevated inflation

TLTOVNQ
+35.1%
+22.4% alpha
5

Defense spending only goes up from here

LMTRTXGD
+44.8%
+31.2% alpha
Beat the Leaderboard →

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