Finviz Alternative

June 24, 2026 · 6 min read

If you are looking for a Finviz alternative, you already know how a screener works. You set the filters — RSI, moving average, volume, a valuation cut — and the software returns every name that cleared them. Finviz Elite adds alerts and a real-time heat map. What it does not do is rank the list based on which setups historically paid off — every name that cleared your filter looks the same as every other one that did, and the filter stays exactly as you drew it until you change it yourself.

Quant-Builder uses those same indicators and trains a machine learning model on them. The model learns which combinations of RSI, moving averages, and volume historically preceded the kind of move you targeted. Each night it scores the entire universe — QB500 covers about 500 large and mid-size US stocks, Healthcare narrows it to one sector, Technology to another — and in the morning Today's Picks is the ranked list. The name at the top is not just a name that cleared a filter. It is the name the model gave the highest probability of working. You can run Healthcare and Technology on the same page at the same time, and the next morning they both score again without you touching anything.

There is no code. You set up the model through a chat interface. Paid plans start at $25 a month. When you are ready to trade, you send directly from the site to Alpaca or TradeStation. Demo at /learn. Paid plans at /pricing.

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The output

This is the table. Ranked. Ready. You do not rebuild the filters each morning.

Healthcare:

Technology. Same page. Different book:

Quant-Builder.ai Today's Picks for the Technology Long six-year model, names ranked by confidence

How the list got there

You build the model once. After that the list updates every morning without you touching anything.

1. Set up the universe and the target

Chat helps you pick the universe, the direction, the training window, and the target. A long Healthcare book, trained on six years, targeting a 3% move in five days, is one example. Technology is the same path with a different universe.

Quant-Builder.ai chat: setting up a model by picking universe, direction, training window, and target, no code

2. Add the indicators you already use

RSI, simple moving averages, volume, valuation — they all sit in the same feature library. You ask chat to add them or pick from the list. You do not write a line of code.

Quant-Builder.ai chat adding simple moving average features to a model from the feature library

3. Train and review the model

The platform trains on the history you set and returns the model page with features, target, and test numbers. You can see exactly what the model learned before it ever scores a live day.

Quant-Builder.ai trained Technology Long six-year model page with features, target, and test numbers

4. Check the backtest

Equity curve and drawdown for that book. Walk-forward is the default, which means the model was never shown the data it is being graded on. You can see how the approach held up across different market conditions before you commit capital to it.

Quant-Builder.ai completed portfolio backtest with equity curve and drawdown

Then you can send

Finviz stops at the list. Here you set the size, the stop, the take profit, and the exit date. You can send more than one lot. In this sitting we buy 1% of each name, twice. Each lot has a 5% stop. One takes profit at 2.5%. The other takes profit at 6%.