12 AI strategies · running live

Watch an AI invest, decision by decision.

AlphaBrain runs 12 investment strategies on simulated $100,000 portfolios. Every trade, the reasoning behind it, and the running return are published here — including when the AI is wrong.

Free forever to follow every strategy, decision, and portfolio. No card required.

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Live AI track record
Running since 25 Aug 2026
Live

Average return

-0.17%

Best strategy

+1.27%

All 12 strategies

Simulated portfolios. Each strategy runs on a hypothetical $100,000 account with no real money at risk, and results do not include the slippage, fees, or fill constraints of live trading. Past and simulated performance does not indicate future results. Nothing here is investment advice.

The proof, not the pitch

Every decision is on the record

Most AI investing tools ask you to trust a score. AlphaBrain publishes what its strategies actually did — what they bought, at what price, and the reasoning at the moment of the trade.

Strategies running

12

Capital each

$100K

Decisions recorded

70

Trades placed

104

Running since 25 Aug 2026.

Most recent trade · Robust Multi-Factor Committee

SELLJNJ$162

“Memo offers no new evidence or recommendation; per the memo, no state-changing action is executed. HOLD explicitly retains the existing JNJ position at its current 7.5% target.”

Free account

See what the AI is thinking, free

The track record is public. Create a free account and you also get the full analysis behind each decision — the data the AI pulled, the alternatives it weighed, and the risks it flagged.

No card required. Upgrade only if you want more.

Every portfolio, live

Holdings, cash, weights, and the running return for all 12 AI strategies.

The full reasoning

The complete analysis behind each trade, not just the one-line rationale.

Your own research

Ask the same engine about any stock or ETF and get a source-linked answer.

Copy a strategy

Run any published strategy against your own portfolio and constraints.

From market noise to portfolio action

AlphaBrain is built around the questions investors actually ask before buying, holding, trimming, or hedging.

Read the market faster
Summarize news, filings, analyst context, and macro headlines into what changed for your holdings.
Price event risk
Use prediction-market odds to understand what investors are assigning probability to before it hits portfolios.
Verify with fundamentals
Check quotes, ratios, statements, earnings, ETF exposure, and valuation data before making a move.
Decide what to do next
Translate signals into watchlist changes, risk checks, rebalancing ideas, and scenario alerts.

Signal chain

Know why a decision makes sense

The product is not another dashboard full of charts. It connects the source, the market implication, and the portfolio action in one inspectable flow.

Find the signal
Pull relevant news, company data, macro context, prediction-market odds, and portfolio exposure.
Rank what matters
Separate facts, assumptions, risk drivers, stale data, and model interpretation.
Take the next step
Get a clear action frame: monitor, research deeper, rebalance, hedge, or create an alert.

Ask better questions

Turn investment intent into research

Start with a plain-English question. AlphaBrain chooses the relevant data sources, runs the analysis, and shows the evidence trail.

What changed today for NVDA and its suppliers?

Is my ETF exposure too concentrated in AI infrastructure?

Compare recession odds with recent macro news.

Which holdings are most exposed to a China-Taiwan shock?

What should I watch before adding to semiconductors?

Create an alert if the thesis breaks.

Built for investment decisions, not content generation

Source-linked output

Claims are tied back to the tool or data source that produced them.

Decision framing

Answers separate facts, assumptions, investment opinion, and portfolio fit.

Inspectable traces

Tool calls and data snapshots stay visible so you can audit the analysis path.

How the decision engine works

Three stages to convert fragmented signals into portfolio context.

Step 01

Connect signals
Bring together news flow, stock and ETF data, macro context, and prediction-market odds.

Step 02

Compare outcomes
Let the AI weigh catalysts, fundamentals, probabilities, and downside risks side by side.

Step 03

Act with context
Get portfolio-aware next steps with assumptions, missing data, and risk narratives attached.

Frequently asked questions

Follow the AI’s next decision

12 strategies, $100,000 each, every trade published with its reasoning. Create a free account to see the full analysis behind each one and run the same engine on your own portfolio.

Simulated portfolios. Each strategy runs on a hypothetical $100,000 account with no real money at risk, and results do not include the slippage, fees, or fill constraints of live trading. Past and simulated performance does not indicate future results. Nothing here is investment advice.