Kavout is an AI stock research platform best known for the K Score, a machine learning rating that ranks stocks daily. It now pairs those rankings with screeners and an AI research assistant, with a free tier and paid plans for individual investors.
Kavout is an AI stock research platform whose signature product is the K Score: a machine learning rating that ranks stocks on a simple scale by crunching fundamentals, price and volume behavior, and other signals, refreshed as new data arrives. A high score means the model likes the stock's odds relative to its peers; a low score means the opposite. Around that core, the Seattle-based company has built screeners, watchlist alerts, and an AI assistant you can ask research questions in plain English.
Worth knowing before you dig in: Kavout has shifted its audience over the years. It originally courted funds and institutions with quantitative services, and today it presents as a research tool for individual investors, with a free tier and self-serve paid plans. The platform remains active in 2026, and reviewers keep covering it, so this isn't one of the zombie AI-finance sites that quietly stopped updating.
Kavout fits self-directed investors who want a quantitative second opinion without building models themselves, and advisors or newsletter writers hunting for idea flow. If you already pay for a full research terminal, Kavout is a supplement, not a substitute; and if you're a pure index investor, a stock-ranking engine solves a problem you don't have.
There's a free tier with limited features, and paid plans start at about $20 a month for Pro, with higher tiers adding more data and AI usage. That puts it in impulse-purchase territory compared with institutional tools, and you can cancel anytime, so trying it for a month is a cheap experiment.
We like the K Score as an input. Ranking the whole market daily by a consistent, emotionless model is genuinely useful for generating candidates and for challenging your own bias about a stock you've fallen in love with. At $20 a month, it costs less than a single bad trade, and the screener-plus-score combination is a sensible workflow.
Our reservations are the ones that apply to every retail quant product, and they're worth stating plainly. The K Score is a black box: you can't inspect why the model likes a stock, and Kavout publishes no independently audited track record of how top-ranked names actually performed after fees and slippage. The company's pivot from institutional services to a retail subscription also tells you the roadmap can change again. Use it to build a short list, then do your own work on valuation and the business before any money moves; treat the score as one voice at the table, never the verdict.
