SEC Filing Analysis Tools Compared: 2026 Guide
By Chad Hartman
Published · Last updated
Every product in this category calls itself a research platform, and almost none of them are solving the same problem. Some search documents. Some license standardized fundamentals and layer a score or a model on top. Some screen a universe by ratio. One extracts what companies actually filed and stops there. The comparisons that read as contradictory ("Platform A is better than Platform B," "no, B is better") are usually two people evaluating tools built for different jobs against the same checklist.
Sorting by function instead of by brand removes most of the confusion. Four categories cover essentially the whole market: document search, normalized and licensed data, as-filed source data, and stock screening. A tool can straddle more than one (TIKR both licenses fundamentals and screens on them), but almost every platform has one category it was actually built to win.
Table of Contents
- The 24 Platforms at a Glance
- Document Search: AlphaSense, BamSEC, Quartr, and Seeking Alpha
- Normalized and Licensed Fundamentals Data
- As-Filed SEC Data
- Stock Screening
- Choosing the Right Category for the Job
- Frequently Asked Questions
The 24 Platforms at a Glance
The categories below are easier to hold in view side by side. "What the number on screen is" is the question that actually separates these products; where a platform has not published or the sections below do not establish where its fundamentals originate, the last column says so rather than guessing.
| Platform | Category | What the number on screen is | Source of fundamentals |
|---|---|---|---|
| AlphaSense | Document search | A cited passage, not a typed fact | Not stated here; structured data sold separately |
| BamSEC | Document search | The figure as it sits in the filing document | SEC EDGAR filings |
| Quartr | Document search | Spoken and IR language, not a computed value | Not stated here |
| Seeking Alpha | Document search / publishing | A contributor's figure inside an argument | Not stated here |
| Bloomberg Terminal | Institutional terminal | A standardized figure mapped for cross-market comparability | Not stated here |
| S&P Capital IQ | Institutional terminal | A standardized figure in S&P's own template | Not stated here |
| FactSet | Institutional terminal | A standardized figure reconciled across sources | Not stated here |
| TIKR | Multi-asset platform + screening | A licensed standardized figure | S&P Capital IQ |
| Koyfin | Multi-asset platform | A licensed standardized figure | S&P Capital IQ |
| YCharts | Advisor-workflow platform | A licensed standardized figure | Licensed dataset; provider not stated here |
| Fiscal.ai | AI research assistant | An AI answer citing a standardized figure | S&P Global Market Intelligence |
| Morningstar | Scoring and rating layer | A star rating built on an analyst fair value estimate | Not stated here |
| GuruFocus | Scoring and rating layer | A GF Score on top of licensed fundamentals | Morningstar-licensed fundamentals |
| Simply Wall St | Scoring and rating layer | A Snowflake shape summarizing five inputs | Not stated here |
| Value Line | Scoring and rating layer | A Timeliness Rank | Not stated here |
| Zacks | Scoring and rating layer | A Rank driven by estimate revisions | Not stated here |
| Daloopa | Model-building | A model-ready KPI with a source hyperlink | Filings, presentations, and transcripts |
| Finbox | Model-building | A model output with consensus-estimate defaults | Standardized data; provider not stated here |
| Wisesheets | Spreadsheet add-in | Whatever the spreadsheet function returns | Not stated here |
| StockAnalysis.com | Free and low-cost aggregator | A standardized figure on a fast page | S&P Global Market Intelligence and Fiscal.ai |
| ROIC.ai | Free and low-cost aggregator | A processed figure at low or no cost | Not stated here |
| Finviz | Screening | A single row of ratios | Not stated here |
| Stock Rover | Screening | A computed metric from a large tier-gated library | Not stated here |
| GeminIQ | As-filed SEC data | The reported fact, with its XBRL tag still attached | SEC EDGAR 10-K and 10-Q filings |
Document Search: AlphaSense, BamSEC, Quartr, and Seeking Alpha
These platforms answer "what has been said," not "what does the number equal." AlphaSense indexes more than 500 million documents (filings, broker research, transcripts, news) and returns cited passages through Generative Search and Deep Research. After the 2024 Tegus acquisition it also carries a large expert-call transcript library. BamSEC is the filing-native member of this group: instead of indexing a corpus, it makes one company's 10-Ks, 10-Qs, and exhibits fast to move through, jumping straight to a section rather than scrolling a raw EDGAR document. The job is navigating the filing itself, which is why it sits here rather than with the data platforms below. Quartr covers the first-party side of the same problem: live earnings calls, transcripts, and IR material, which is where management's tone and word choice live and no filing ever will. Seeking Alpha is different again: a publishing platform with data attached, where thousands of contributors produce more than 10,000 articles a month, which means every thesis on the site has a counter-thesis sitting next to it.
All four are retrieval tools. A search index ranks passages by relevance and returns the ones most likely to answer a query; it cannot rank fifteen thousand filers by a metric, because ranking requires the value to exist as a typed fact rather than as characters inside a paragraph. That is a structural boundary, not an execution gap. AlphaSense sells structured financial data and models as a separate add-on for exactly this reason.
Normalized and Licensed Fundamentals Data
This is the largest and most crowded category, and nearly every platform in it starts from the same move: map each company's reported line items into a standardized, cross-company template. That makes comparison fast. It also means the number on screen answers "what is the standardized figure," not "what did the company file."
Institutional Terminals: Bloomberg, S&P Capital IQ, and FactSet
Bloomberg Terminal and S&P Capital IQ are the standard seats on a trading desk: global coverage, credit analytics, estimates, entity resolution across accounting regimes, none of which a filings-only product replicates. Neither publishes pricing; third-party procurement trackers commonly place a Bloomberg seat in five figures annually, and Capital IQ Pro is quote-only. FactSet sits in the same tier, solving the same reconciliation problem for firms running multiple data sources that have to agree with each other.
Broad Multi-Asset Platforms
TIKR and Koyfin both license Capital IQ fundamentals underneath a broader research workspace. TIKR emphasizes global screening, valuation templates, and transcripts across 100,000+ stocks and 92 countries; Koyfin adds portfolio tools, macro dashboards, and client reporting, with paid tiers starting at $39 a month. YCharts targets advisor and wealth-management workflows on the same kind of licensed dataset. Fiscal.ai (the platform formerly known as FinChat) puts a citation-backed AI research assistant on top of S&P Global Market Intelligence data, which answers questions well but is only ever as accurate as what the AI is reading.
Scoring, Rating, and Estimate Layers
Morningstar, GuruFocus, Simply Wall St, Value Line, and Zacks each compress fundamentals into a single output: a star rating, a GF Score, a Snowflake shape, a Timeliness Rank, a consensus-revision Rank. Every one of them is a real, useful filter, and every one of them is a conclusion rather than a measurement. Morningstar's star rating runs on an analyst's fair value estimate and an assumed cost of capital that appears in no filing. GuruFocus stacks a proprietary score on top of Morningstar-licensed fundamentals. Zacks Rank tracks estimate revisions, which is a different clock entirely from what a business actually earned. None of the five inputs behind these systems is purely a number the company reported.
Model-Building and Spreadsheet Tools
Daloopa, Finbox, and Wisesheets solve the "get the data into my model" problem rather than the "what does the filing say" problem. Daloopa extracts model-ready KPIs from filings, presentations, and transcripts with source hyperlinks and better than 99% claimed accuracy across roughly 6,000 tickers. Finbox prebuilds DCF, dividend discount, and comparable-company models on standardized data with consensus-estimate defaults, starting around $10 a month. Wisesheets pulls fundamentals into Excel or Google Sheets through a spreadsheet function. All three are genuinely fast. None of them changes what data sits underneath the formula.
Free and Low-Cost Aggregators: StockAnalysis.com and ROIC.ai
StockAnalysis.com is the standout here, with clean, fast pages, minimal advertising, coverage past 130,000 symbols, and unusually candid documentation about its own architecture. Its data-sources page names S&P Global Market Intelligence and Fiscal.ai as providers and tells users to confirm critical figures against the original filing before acting on them. Almost nobody follows that instruction, because doing it by hand takes roughly fifteen minutes per figure.
ROIC.ai occupies the same slot from the other direction, aimed at investors who want statements and ratios without a subscription decision attached to the first look. The category economics hold either way: what a low-cost aggregator displays is a processed figure, and the price is low partly because the processing was done once, upstream, for everybody.
As-Filed SEC Data
This category has exactly one kind of entrant: a platform that extracts directly from SEC EDGAR and stops there. GeminIQ pulls 10-K and 10-Q data straight from the filing, preserves each company's own reported line-item structure, and keeps the XBRL tag attached to every value. A Free plan carries 3 years of history and 24 calculated metrics on that same pipeline at no cost; the paid Annual and Monthly plans extend it to 17-plus years, 90-plus metrics, and the Stock Screener. There is no mapping layer between the filing and the display, no template deciding which line items get combined, and no score sitting between the number and the reader.
That scope is deliberately narrow. No global coverage, no credit analytics, no analyst estimates, no expert-call library. What it buys instead is that a figure on screen is the reported fact rather than a representation of one. Financial Statements show a company's own captions across quarters and years, Custom Tables assemble specific reported line items, Visualizations chart the reported structure over time, and Calculated Metrics compute from those as-filed inputs rather than from a template's definition. The verification step every platform above tells its users to run ("confirm against the primary source") is the default state here instead of a fifteen-minute errand.
Stock Screening
Screening is a distinct job from either search or normalization: reduce a universe to a shortlist using computed, filterable values. Finviz does it fastest and cheapest: a free tier used by roughly 25 million people a month, with Elite adding real-time data at $299.50 a year. Its fundamental layer, though, is a single row of ratios with history capped at three years free, eight on Elite. Stock Rover is the deepest pure screener, with somewhere between 275 and 800+ metrics depending on tier and up to twenty years of history, though tier-gating means the analytical question you can ask is partly set by what you paid.
Several of the licensed platforms above bundle screening on top of their normalized data (TIKR and Capital IQ both do), which means the screen inherits whatever mapping decisions sit underneath it. A screen is only as good as the fields behind it. GeminIQ's Stock Screeners run the same filtering operation directly against as-filed, XBRL-tagged data, including named strategy screens like the Magic Formula Screener and the Piotroski F-Score Screener. A company that passes can be checked against the filing that produced the result without ever switching platforms.
Choosing the Right Category for the Job
Most of the frustration investors report with financial data tools traces back to using one category to answer a question built for another. A search platform cannot rank a universe. A scoring layer cannot show you why a company scored the way it did. A spreadsheet formula cannot tell you which XBRL tag produced the value it returned. None of that is a product failure. It is a category boundary, and every platform above is genuinely strong at the job it was built for.
The categories are not mutually exclusive in practice, and a serious research process typically uses more than one: search to shape the question, a licensed platform to screen broadly and fast, and the primary filing to settle anything a decision is actually going to rest on. As-filed data is not a replacement for the other three categories. It is the one category none of the other three can substitute for, because it is the only one answering what the company actually reported rather than what a representation of that report says.
Frequently Asked Questions
What's the difference between normalized and as-filed SEC data?
Normalized data has been mapped by a third-party provider into a standardized template so companies can be compared on the same line items. As-filed data preserves the company's own reported structure and XBRL tags exactly as submitted to the SEC. Normalization aids comparability; it can also combine, split, or relabel items in ways that change what a figure represents.
Which SEC filing analysis tool is best for stock screening?
It depends on depth versus breadth. Stock Rover offers the deepest metric library among dedicated screeners; Finviz is the fastest and cheapest for a quick scan; several licensed platforms like TIKR and Capital IQ bundle screening with normalized fundamentals. Every screen is only as reliable as the data field it filters on.
Do any SEC filing research platforms show data straight from EDGAR with no normalization?
That is a narrow category by design. GeminIQ extracts 10-K and 10-Q data directly from SEC EDGAR and preserves each company's own reported line items and XBRL tags without a standardization layer in between.
Is document search the same as fundamental analysis?
No. Document search retrieves relevant passages from filings, research, and transcripts; fundamental analysis requires structured, computable values that can be sorted, filtered, and compared across periods and companies. Search platforms like AlphaSense are explicit that this is a different problem; several sell structured data and modeling as a separate product line.
What is financial data normalization software?
In this context, normalization means mapping each company's own reported line items into one standardized, cross-company template so the same row means the same thing for every filer. It is not the data-science sense of the word, which rescales values into a common numeric range, and it is not normalized EBITDA, which adjusts a single company's earnings for items an analyst judges non-recurring. Every platform in the normalized and licensed category above performs the first kind. The trade is always the same: comparison gets faster, and the figure on screen becomes the standardized version of what the company filed rather than the filing itself.
Which SEC filing analysis tools are free?
SEC EDGAR is free and always has been, including the XBRL data behind every reported figure, though it leaves the extraction work to you. Among the commercial tools above, Finviz runs a genuine free tier used by roughly 25 million people a month, StockAnalysis.com and ROIC.ai are free to browse, and GeminIQ's Free plan carries 3 years of as-filed history and 24 calculated metrics at no cost on the same pipeline as its paid plans. The institutional terminals publish no pricing at all, free or otherwise.
What happened to QuickFS?
QuickFS has shut down. Its homepage is now a farewell note from founder Ted Cooper pointing users to FastFS.org. For investors looking for a replacement, the practical question is which category the tool was filling: if it was standardized statement history, the licensed and low-cost aggregators above cover it, and if it was traceability back to the filing, that is the as-filed category rather than a like-for-like swap.
Wall Street's data. Main Street's price.
Institutional terminals charge thousands a year for as-filed accuracy. GeminIQ gives you the same thing for a fraction of the cost: financials built directly from raw SEC EDGAR filings, not third-party APIs, with full XBRL traceability back to the original 10-K or 10-Q. No normalized guesswork, just calculated metrics, charts, screeners, and watchlists built on numbers exactly as the company reported them. Start researching now at GeminIQ.com.
Data Used / Sources
- Fundamental data sourced from XBRL-tagged SEC filings via GeminIQ.
- Category placements and figures for AlphaSense, BamSEC, Quartr, Seeking Alpha, Bloomberg Terminal, S&P Capital IQ, FactSet, TIKR, Koyfin, YCharts, Fiscal.ai, Morningstar, GuruFocus, Simply Wall St, Value Line, Zacks, Daloopa, Finbox, Wisesheets, StockAnalysis.com, ROIC.ai, Finviz, and Stock Rover are drawn from GeminIQ's own published comparison research on each platform (linked above), reviewed August 2, 2026 from each platform's public materials and third-party reviews. Verify current pricing and plan details on each vendor's site before republication.
- GeminIQ Free, Annual, and Monthly plan features, limits, and pricing confirmed directly from https://www.geminiq.com/pricing, retrieved August 8, 2026.
Disclaimer: The content in this blog is for educational and entertainment purposes only and does not constitute financial, legal, or tax advice. Investing involves risk, including the loss of principal. The views expressed are my own and not intended as financial advice or a guarantee of future performance.