# AI stock analysis tools compared: score, coverage, and what happens when they're wrong - **Source:** Synoptiv (https://synoptiv.com) - **Canonical URL:** https://synoptiv.com/insights/ai-stock-tools-compared - **Section:** Method & transparency - **Published:** 2026-09-13 - **Updated:** 2026-09-13 - **Reading time:** 7 min ## Summary As of September 2026, almost every AI stock analysis tool on the market outputs a score: Danelfin an AI Score of 1-10, Kavout a Kai Score of 1-9, Zen Ratings a letter grade from A to F, Simply Wall St a visual snowflake across five dimensions. They differ mainly in how much of the market they cover — from a few hundred symbols to over 120,000 — and in how much of the reasoning behind the number they show you. The question that separates them in practice is not accuracy, which none of them can prove to you in advance, but falsifiability: whether the tool states the specific conditions under which its own conclusion would be wrong. Most do not. --- > **Prices change frequently and vendors update tiers without notice, so this comparison > deliberately contains no prices.** Check each vendor's own pricing page before buying. > Everything below describes capability and design, which changes far more slowly. Facts > stated here were checked on 13 September 2026. This article names competitors and compares them directly. Its companion piece, [how to choose an AI stock analysis tool](/insights/ai-stock-analysis-tools), covers the same market by *category* rather than by name — read that one if you are still working out what kind of tool you need. This one assumes you know that and want to know how the specific products differ. We make one of these products, so read the section on where Synoptiv is worse before you read anything else here. ## What each tool actually hands you The category is less varied than the marketing suggests. Strip away the presentation and almost everything here is a ranking engine that converts many inputs into one number. | Tool | Primary output | Universe | Reasoning shown | |---|---|---|---| | Danelfin | AI Score 1-10 (probability of beating the market over ~3 months) | US above ~$2B market cap; 5,500+ European stocks | Factor attribution — which indicators drove the score | | Kavout | Kai Score 1-9, daily | ~9,000 US stocks, plus crypto | Score and rank, with a screener | | Zen Ratings | Letter grade A-F across 115 factors | Broad US coverage | Component factor grades | | Simply Wall St | Visual "snowflake" across five dimensions | 120,000+ stocks, 90+ markets | Visual breakdown per dimension | | Seeking Alpha | Human-written articles plus quant grades | Broad US coverage | Full human argument, variable quality | | Synoptiv | Written analysis with a stated position | A few hundred US symbols | The full argument, plus what would invalidate it | Two honest observations about that table. First, **the scoring tools are not really competing with the writing tools.** A score answers "how does this rank against everything else?" An analysis answers "what is the argument here, and where is it weak?" People who buy one expecting the other are predictably disappointed, and that is a category error rather than a product failure. Second, **coverage and depth are in direct tension.** Scoring 120,000 companies is a data-pipeline achievement. It is not the same activity as reading a company's filings and forming a view. Neither is better in the abstract; they are different jobs. ## Buyer question 1: do you need breadth or depth? If your problem is "there are 5,000 candidates and I need 20," you want breadth, and a scoring tool with a screener is the correct purchase. Danelfin, Kavout, and Zen Ratings all do this well, and Synoptiv does not do it at all — there is no screener, and the universe is too small to screen. If your problem is "I have five candidates and I need to understand each one properly," breadth stops helping. At that point what matters is how much of the reasoning you can inspect and check. Most people need both, at different moments, which is why the tools coexist rather than displacing one another. ## Buyer question 2: a score, or an argument? A score's great virtue is that it is fast. Its great weakness is that it is unfalsifiable in practice. If a stock rated 9/10 falls 30%, nothing about the rating was *wrong* in a way you can point to — the score was a probability, probabilities are sometimes disappointed, and the model simply re-scores tomorrow. This is not dishonest. It is a structural property of compressing an argument into a number. An argument carries the opposite trade. It takes ten minutes to read instead of one second, and it can be checked. If the analysis says a company's margin expansion depends on a specific input cost staying flat, you can go and look at that input cost. You cannot audit a 9. Our [AI analysis](/glossary/ai-analysis) is written rather than scored for exactly this reason, but we would rather you understood the trade-off than took our word for which side of it to be on. ## Buyer question 3: does it tell you what would change its mind? This is the question we think matters most, and it is the one the category answers worst. Across the tools surveyed here, we found none that publish explicit [invalidation conditions](/glossary/invalidation) — the specific, checkable things that, if they happened, would mean the conclusion no longer holds. Scores update silently. Ratings move from A to B without a moment where the previous rating is marked wrong. Why this matters more than it sounds: a view that cannot be wrong cannot teach you anything. If you hold a position because a tool rated it highly, and the rating quietly drops six weeks later, you have learned nothing about *why*, and you have no basis for deciding whether your original reasoning was flawed or the world simply changed. We also publish a [no-trade](/glossary/no-trade) outcome — an explicit "the evidence here is mixed, we do not have a view" — which is rare because it is commercially unattractive. A tool that produces a confident answer every time is easier to sell than one that sometimes declines. ## Buyer question 4: can you see what it said last month? Most tools present a current state. Yesterday's score is gone. Synoptiv versions each analysis rather than overwriting it, so an [earlier version](/glossary/analysis-version) stays on the record with its date. The point is not that our old analyses are good — some of them will be wrong — but that they remain inspectable, which is the only way anybody could ever hold the product accountable. If you are evaluating any tool in this category, ask whether you can retrieve what it told you three months ago. The answer is more revealing than any accuracy claim. ## On performance claims — including the ones we don't make Several competitors publish backtested performance figures. Danelfin reports annualised alpha for its top-decile scores since 2017; Zen Ratings reports annual returns for A-rated stocks since 2006. These numbers may well be computed correctly. They are also vendor-published, largely [backtested rather than live](/glossary/hypothetical-performance), and not independently audited — three qualifications that do a great deal of work. Synoptiv publishes no performance claim at all. Not out of modesty: our [track record](/glossary/track-record) is too short and the sample too small for any number we produced to mean anything, and publishing one anyway would be the single most misleading thing we could do. When the sample is large enough, we will publish it including the bad parts. The general rule, applied to us as much as anyone: **a performance figure you cannot reproduce is an advertisement.** ## Where Synoptiv is worse Stated plainly, because a comparison written by a vendor that omits this is not worth reading. | Weakness | Detail | |---|---| | Coverage | A few hundred US symbols against Kavout's ~9,000 and Simply Wall St's 120,000+. This is the biggest gap and it is not close. | | No screener | No way to filter a universe by criteria. If that is your job to be done, buy something else. | | No mobile app | Web only. | | No international coverage | US-listed symbols only. Danelfin and Simply Wall St both cover Europe. | | No track record | The product is new. Competitors cite multi-year backtests; we cite nothing, which is honest but not reassuring. | | Slower to consume | Reading an argument takes longer than glancing at a number, and sometimes a number is genuinely what you need. | If you want whole-market coverage, a screener, or a phone app, the honest answer is that one of the other tools on this page is a better fit today. ## How to check any of this yourself Everything above is verifiable, and you should verify it rather than trust a comparison written by a participant: 1. **Open each vendor's own pricing and features page.** Third-party review sites carry affiliate incentives and go stale fast. 2. **Ask each tool for its reasoning on a stock you already know well.** You will spot a confident error far faster in a company you understand. 3. **Ask what would have to happen for the tool to be wrong.** Note whether you get a specific answer or a restatement of the conclusion. 4. **Try to retrieve what it said last quarter.** 5. **Check whether numbers are computed or generated.** In a serious tool, financial figures are calculated deterministically from source data and the language model writes only the prose around them. Where the model produces the numbers too, they are occasionally plausible and wrong. Points 3 and 4 are the ones almost nobody applies, and they are the ones that separate a research tool from a confident-sounding interface. *Not investment advice. Synoptiv produces research, not recommendations, and nothing here is a suggestion to buy or sell any security. Competitor facts were checked on 13 September 2026 from vendor and public sources; capabilities and pricing change, so verify before purchasing.* --- ## Common questions ### Which AI stock analysis tool covers the most stocks? Simply Wall St covers the widest universe, reporting more than 120,000 stocks across 90+ markets. Kavout analyses roughly 9,000 US stocks daily. Danelfin covers US stocks above about $2B in market capitalisation plus more than 5,500 European stocks after its February 2026 expansion. Synoptiv is the smallest of the group at a few hundred US symbols. Coverage and depth trade off against each other: a tool that scores 120,000 companies is not reading 120,000 annual reports. ### Do AI stock tools publish their track record? Several publish backtested figures — Danelfin reports annualised alpha for its top-scored stocks since 2017, and Zen Ratings reports returns for A-rated stocks since 2006. These are vendor-published and largely backtested rather than independently audited, which is a materially different thing from a live, third-party-verified record. Treat any performance number you did not compute yourself as a marketing claim until you can reproduce it. ### What is the difference between a stock score and a stock analysis? A score compresses many inputs into one number, which makes it fast to scan and impossible to argue with. An analysis states a position and the reasoning behind it, which is slower to read and possible to disagree with. Scores are better for narrowing a large universe to a shortlist. Analyses are better for the decision you make at the end of that shortlist, because you can check whether the argument actually holds. ### Is there an AI stock tool that says when it is wrong? This is the least common feature in the category. Most tools silently update a score when conditions change, which means there is no moment at which the previous view is marked incorrect. Synoptiv publishes explicit invalidation conditions with each analysis and versions the analysis rather than overwriting it, so a prior view stays on the record. We built it that way because we think it is the honest design, but it is a claim you should verify rather than take from us. ## Related terms - https://synoptiv.com/glossary/ai-analysis - https://synoptiv.com/glossary/invalidation - https://synoptiv.com/glossary/analysis-version - https://synoptiv.com/glossary/track-record - https://synoptiv.com/glossary/hypothetical-performance - https://synoptiv.com/glossary/no-trade - https://synoptiv.com/glossary/sentiment - https://synoptiv.com/glossary/technical-indicators ## About this source Synoptiv publishes versioned AI-assisted analysis of US stocks for individual investors, alongside a public glossary and methodology. Analysis and education only — nothing here is investment advice or a recommendation to buy or sell any security. - Methodology: https://synoptiv.com/methodology - Disclosures: https://synoptiv.com/disclosures - All insights: https://synoptiv.com/insights - Analyzed stocks: https://synoptiv.com/stocks