// edgar.financials.query { 1"ticker": "AAPL", 2"period": "annual", 3"filingType": "10-K", 4"income": { 5 "revenue": 383285000000, 6 "grossProfit": 169148000000, 7 "netIncome": 99803000000, 8 "eps": 6.43 9}, 10"normalized": true }
// data.transform.pipeline async function processFilings(tickers) { 1 const results = []; 2 for (const sym of tickers) { 3 const raw = await edgar.fetch(sym); 4 const norm = normalize(raw); 5 results.push({ ticker:sym, data:norm }); 6 } 7 return exportDataset({ json,excel }); }
// macro.fred.timeseries { 1"series": "CPIAUCSL", 2"frequency": "monthly", 3"source": "FRED · St. Louis", 4"data": [ 5 {"date":"2024-12","value":314.8,"yoy":2.9}, 6 {"date":"2024-11","value":314.1,"yoy":2.7}, 7 {"date":"2024-10","value":313.5,"yoy":2.6} 8], 9"normalized": true }
// screener.query SELECT ticker, net_margin, pe_ratio 1FROM edgar.fundamentals 2WHERE net_margin > 0.20 3 AND pe_ratio < 30 4 AND sector = 'Technology' 5ORDER BY free_cashflow DESC; 6-- 12 results matched
Data ProcessingTransforming
1 { 2 "ticker": "AAPL", 3 "filingType": "10-K", 4 "income": { 5 "revenue": 383285000000, 6 "netIncome": 99803000000, 7 "eps": 6.43 8 }, 9 "normalized": true 10 }
Transformation Script
1 async function process(t) { 2 const raw = await edgar.fetch(t); 3 const norm = normalize(raw); 4 return export({ json,excel }); 5 }
SEC EDGAR Intelligence · Free to use

Institutional analysis,
no paywall.

Every tool you need to analyze a stock — technical indicators, risk metrics, SEC fundamentals — available instantly, without signing up.

Get Started See all features ↓
20+
Technical indicators
7+
Risk metrics tracked over time
320
US tickers covered
0$
Cost to get started
Platform

Every tool
in one place.

From price action to balance sheets. No sign-up walls, no paywalled metrics.

∿

Technical Analysis

RSI, MACD, Bollinger Bands, OBV, CCI — interactive time-series with interpretation panels.

◈

Risk Metrics

Sharpe, Sortino, Max Drawdown, VaR, Beta and Alpha — tracked over time, not as single numbers.

∑

SEC Fundamentals

10-K and 10-Q filings structured into income, balance sheet, and cashflow tables with 5-year trends.

⟳

Momentum Suite

ADX, Stochastic, Williams %R, ROC — a full suite for trend strength and reversals.

⊞

Stock Screener

Filter by fundamentals, technicals, and risk metrics simultaneously to surface the right opportunities.

⌖

Insight Chart

SMA, EMA, Bollinger Bands overlays, volume bars, scroll-to-zoom — all on one precision canvas.

SEC EDGAR

Filings,
structured.

10-K and 10-Q filings parsed, normalized, and displayed as clean tables and charts.

nivvuro — edgar.financials · live query
TickerCompanySectorRevenue (TTM)Net MarginP/EFree CFΔ 30d
AAPLApple Inc.Tech$383.3B26.4%28.9$99.6B+4.2%
MSFTMicrosoft Corp.Tech$227.6B35.8%34.2$70.1B+6.7%
JPMJPMorgan ChaseFinance$158.1B31.2%12.1—−1.8%
JNJJohnson & JohnsonHealth$88.9B18.6%16.4$14.2B+1.1%
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20 US companies across sectors, 5 years of annual fundamentals plus ratios.

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Apple, Nvidia, Google, Meta and ~30 more US tech companies, 7 years annual.

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JPMorgan, Goldman, BlackRock and ~30 US financial companies, 7 years annual.

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Deep Pack — JSON

20 US companies, 10-year history. Full schema, all fields. Built for developers.

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20 US companies, 10-year history. Pre-formatted dashboard with charts. Built for analysts.

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All 320 covered US tickers, 5 years of annual data. The complete Nivvuro fundamental dataset.

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Why Nivvuro

Why not just use
SEC EDGAR directly?

◉

Raw EDGAR is XBRL

SEC filings are raw XBRL — inconsistent tagging across companies and years, missing fields, and formats that require parsing expertise to use.

EDGAR raw
XBRL tags inconsistent
Fields missing or null
Needs parsing library
Nivvuro
Normalized field names
Gaps filled or flagged
Open in Excel or Python
⏱

Hours vs. seconds

Fetching, parsing, and cleaning a single company's 5-year filing history from EDGAR takes hours. Nivvuro delivers it as a clean file in seconds after purchase.

DIY
4–8 hrs setup per company
Manual schema mapping
Breaks on filing updates
Nivvuro
Instant download
Standard schema
Updated quarterly
€

No API costs

Alternatives like Financial Modeling Prep or Intrinio start at $99/month. Nivvuro sells the data you actually need, once, for under €60. No monthly commitment.

API services
$99–$299/month
Rate limits per plan
Lose access if cancel
Nivvuro
€2–€60, once
No rate limits
Yours forever
Use Cases

Who buys
Nivvuro data?

🎓
Student / Researcher
"I need clean data for my thesis"

Running a regression on 20 companies' fundamentals? The Single Ticker or Starter Pack at €2–€15 is cheaper than any API and ready to import into Python or R immediately.

📰
Newsletter Author / Analyst
"I write about markets weekly"

Grab the US Tech or Finance Sector pack once. Build your own comparison tables, charts, and rankings — without a recurring API bill eating into your margins.

⚙️
Developer / Indie Hacker
"I'm building a fintech tool"

The Deep Pack JSON gives you a full normalized schema to prototype against — before committing to an expensive data API contract. Ship your MVP first.

FAQ

Common
questions.

Why buy this instead of going to SEC EDGAR directly?▾
EDGAR's raw data is in XBRL format — inconsistent across companies and years, requiring significant technical work to parse and normalize. Nivvuro delivers the same data already cleaned, standardized, and ready to open in Excel or load into Python. For most users, the time saved is worth multiples of the price.
What exactly do I receive after purchase?▾
An immediate download link on the confirmation page and by email. You get a ZIP file containing a JSON file (machine-readable, for Python/JS/R) and an Excel file (formatted with separate sheets per statement, ready to use). No account creation required.
How current is the data?▾
Fundamental datasets are updated within 48–72 hours of each SEC filing publication. Macro datasets (FRED, ECB) are refreshed monthly after each agency release. Each dataset card shows the exact last update date before you buy.
Can I use this data commercially?▾
The underlying data (SEC filings, FRED series) is public domain. Nivvuro's value-add is the normalization and packaging. You may use the datasets in your own research, tools, and publications. Redistribution of the raw dataset files for sale is not permitted.
What if the data has an error?▾
Report it via the contact page with the ticker and field name. Verified data errors are corrected and a fresh download link is issued at no charge. Note: differences from reported figures are always traceable to the original EDGAR filing.
Is there a refund policy?▾
Because the files are delivered immediately upon purchase, refunds are generally not offered after download. This is why a free sample dataset (AAPL, 5 rows) is available — use it to verify format compatibility before buying.
USA · SEC EDGAR
Dataset
What's included

    Preview of 3 rows from the dataset. Remaining rows are blurred — purchase to unlock.

    Purchase unlocks all rows · Download as JSON + Excel

    €—
    one-time · instant download
    Nivvuro · Manifesto

    Financial data
    was never meant
    to be a privilege.

    This is what we believe. Why we built Nivvuro the way we did. And what we refuse to become.

    01

    The data is public.
    The access isn't.

    Every 10-K, every 10-Q, every balance sheet of every public US company is filed with the SEC and available to anyone. Free of charge. By law. This is not a secret.

    And yet the industry built a wall around it. Bloomberg charges $24,000 per year for a terminal. Refinitiv, FactSet, Capital IQ — thousands more. The argument is always the same: the data requires cleaning, normalization, expertise. Fair enough.

    But somewhere between "public filing" and "institutional terminal" a decision was made — not a technical one, but a business one — to make that expertise expensive. To charge for access, not just for work.

    The raw data costs nothing. The people who can use it pay everything. That gap is a choice — and it doesn't have to exist.

    02

    Good analysis depends on
    thinking, not budget.

    A student writing a thesis on capital structure shouldn't need a $99/month API subscription to get Apple's balance sheet for the last five years. A freelance analyst writing a market newsletter shouldn't lose margin to data fees. A developer building a financial tool shouldn't pay institutional prices to prototype an idea.

    The quality of insight has never depended on how much someone spent on data. It depends on how they think about it. Nivvuro's position is simple: the data should get out of the way so the thinking can happen.

    03

    No paywall. No login.
    No exceptions.

    The Nivvuro analytics platform is free. Not "free tier with 5 requests" free. Not "free for 14 days" free. Free — because the analysis tools are built on public data, and charging for access to public data dressed up as a product is something we decided not to do.

    You don't need an account to run a DCF screener. You don't need a subscription to check a company's free cash flow trend. You open the dashboard and use it. That's the entire policy.

    A paywall is a statement about who you think deserves information. We've made a different statement.

    04

    We sell the work,
    not the access.

    The datasets we sell are different. Parsing EDGAR's raw XBRL output, normalizing inconsistent field names across thousands of filings, aligning fiscal years, computing ratios, packaging it all into something you can open in Excel or load into Python in five minutes — that is real work. We charge for that work. Once.

    No subscription. No monthly fee. No access revoked if you cancel. You buy the dataset, you own it. If the data updates and you want the new version, you buy the update. That's the deal — honest and explicit.

    05

    What we refuse
    to become.

    We won't introduce a "Pro" tier that locks features behind a paywall that used to be free. We won't sell advertising. We won't sell usage data. We won't raise prices and call it "value alignment." We won't become the thing we were built against.

    These aren't promises made lightly. They're constraints we've set on ourselves deliberately — because the easiest path for any data product is to gradually become another Bloomberg for people who can't afford Bloomberg. We're not interested in that path.

    The measure of a data platform isn't what it charges. It's what it refuses to charge for.

    If this resonates —
    you're who we built this for.

    Students, independent analysts, developers, researchers. People who think carefully about markets and don't have $24,000 to spend on a terminal. Nivvuro exists because of you, and for you.

    Open the platform Browse datasets →
    Written by the Nivvuro team · 2025 · Schmitten, Germany