SEC Filings Intelligence - 10-K Decoded for AI Agents

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The SEC decoder AI agents trust. Extract structured financials, risk factors, executive compensation, and MD&A from 10-K, 10-Q, 8-K, and proxy statements. Built for Colorado SB 25B-004 compliance.

👁 Apify Actor
👁 License: MIT

Why SEC Filings Intelligence?

Problem: SEC filings are goldmines of financial intelligence, but they're trapped in complex HTML and XBRL formats. AI systems need clean, structured, citable data - not 200-page PDFs.

Solution: SEC Filings Intelligence decodes 10-K, 10-Q, 8-K, and proxy statements into structured data with:

• Financial Metrics - Revenue, EPS, margins, and ratios extracted and normalized
• Risk Factor Analysis - Item 1A parsed with categorization and materiality scoring
• Executive Compensation - Named officer pay tables with equity awards
• MD&A Insights - Management discussion decoded into key themes
• RAG-Ready Chunks - 800-1200 token segments optimized for financial Q&A
• Bluebook Citations - Legal-grade citations for every data point

Colorado SB 25B-004 Compliance

Effective June 30, 2026, Colorado's AI Transparency Act requires AI systems to provide meaningful explanations and source attribution. SEC Filings Intelligence delivers:

• ✅ Full provenance - SEC accession numbers and filing URLs
• ✅ Content hashing - SHA-256 fingerprints for verification
• ✅ Legal citations - Bluebook format for regulatory compliance
• ✅ Audit trail - Complete extraction metadata

Task Modes

Quick Start

Basic Usage

const input ={
taskMode:"investor_research",
tickers:["AAPL","MSFT","GOOGL"],
dateRange:"1y",
maxFilings:5
};

Risk Analysis

const input ={
taskMode:"risk_analysis",
tickers:["TSLA"],
extractRiskFactors:true,
comparePriorYear:true,
dateRange:"3y"
};

Executive Compensation Intel

const input ={
taskMode:"compensation_intel",
tickers:["NVDA","AMD","INTC"],
extractCompensation:true,
filingTypes:["DEF 14A","10-K"]
};

Full Intelligence Mode

const input ={
taskMode:"full_intelligence",
tickers:["META"],
extractFinancials:true,
extractRiskFactors:true,
extractMDA:true,
extractCompensation:true,
extractBusinessSegments:true,
extractFootnotes:true,
includeExhibits:true,
ragChunkSize:1000
};

Output: SEC Intelligence Pack

Every extraction produces a comprehensive "SEC Intelligence Pack":

{
"runId":"abc123",
"taskMode":"investor_research",
"filing":{
"ticker":"AAPL",
"companyName":"Apple Inc.",
"cik":"0000320193",
"filingType":"10-K",
"filedDate":"2025-11-01",
"fiscalYear":"2025",
"accessionNumber":"0000320193-25-000123",
"filingUrl":"https://www.sec.gov/Archives/edgar/data/320193/..."
},
"financials":{
"incomeStatement":{
"revenue":394328000000,
"revenueFormatted":"$394.3B",
"costOfRevenue":214137000000,
"grossProfit":180191000000,
"grossMargin":0.457,
"operatingIncome":118658000000,
"operatingMargin":0.301,
"netIncome":93736000000,
"netMargin":0.238,
"eps":6.11,
"epsFormatted":"$6.11"
},
"balanceSheet":{
"totalAssets":364980000000,
"totalLiabilities":290437000000,
"shareholdersEquity":74543000000,
"cash":29965000000,
"debt":111088000000,
"debtToEquity":1.49
},
"cashFlow":{
"operatingCashFlow":122151000000,
"capex":-10959000000,
"freeCashFlow":111192000000,
"dividendsPaid":15025000000,
"shareRepurchases":77550000000
},
"yoyComparison":{
"revenueGrowth":0.028,
"netIncomeGrowth":-0.034,
"epsGrowth":0.012
}
},
"risks":{
"count":34,
"categories":{
"operational":12,
"financial":8,
"regulatory":6,
"competitive":5,
"technology":3
},
"topRisks":[
{
"id":"risk_001",
"title":"Global Economic Conditions",
"category":"financial",
"materiality":"high",
"summary":"Adverse macroeconomic conditions could materially affect...",
"isNew":false,
"changedFromPrior":true
}
],
"newRisks":[],
"removedRisks":[]
},
"compensation":{
"executivesCount":5,
"totalCompensation":98734521,
"executives":[
{
"name":"Tim Cook",
"title":"CEO",
"salary":3000000,
"bonus":0,
"stockAwards":75000000,
"optionAwards":0,
"nonEquityIncentive":12000000,
"otherComp":1386671,
"total":91386671,
"payRatio":"1:1551"
}
],
"equityPlan":{
"sharesAuthorized":1500000000,
"sharesAvailable":245000000
}
},
"mda":{
"summary":"Management highlights iPhone revenue growth of 6% driven by...",
"keyThemes":[
"Services growth acceleration",
"Supply chain normalization",
"Capital return program expansion"
],
"outlook":"Management expects continued growth in Services segment...",
"keyMetrics":[
{"metric":"Services Revenue","value":"$85.2B","growth":"+14%"}
]
},
"segments":[
{
"name":"Americas",
"revenue":169658000000,
"percentOfTotal":0.43,
"growth":0.02
},
{
"name":"Europe",
"revenue":101325000000,
"percentOfTotal":0.26,
"growth":0.01
}
],
"citations":{
"bluebook":"Apple Inc., Annual Report (Form 10-K) (Nov. 1, 2025).",
"apa":"Apple Inc. (2025). Annual Report (Form 10-K). U.S. Securities and Exchange Commission. https://www.sec.gov/...",
"mla":"Apple Inc. \"Annual Report (Form 10-K).\" SEC EDGAR, 1 Nov. 2025, https://www.sec.gov/...",
"inline":"[Apple Inc. 10-K (2025)](https://www.sec.gov/...)",
"bibtex":"@misc{apple2025_10k, author={Apple Inc.}, title={Annual Report (Form 10-K)}, year={2025}, url={https://www.sec.gov/...}}"
},
"chunks":[
{
"id":"chunk_001",
"text":"Apple Inc. reported total net sales of $394.3 billion for fiscal 2025...",
"tokenCount":987,
"section":"Financial Highlights",
"metadata":{
"filing_type":"10-K",
"ticker":"AAPL",
"section":"Item 7 - MD&A",
"fiscal_year":"2025"
}
}
],
"quality":{
"overallScore":94,
"financialsCompleteness":98,
"riskExtraction":92,
"compensationParsing":95,
"citationCoverage":100
},
"summary":{
"oneLiner":"Apple 10-K FY2025: $394B revenue (+2.8% YoY), $6.11 EPS, 34 risk factors, CEO comp $91M",
"keyHighlights":[
"Revenue: $394.3B (+2.8% YoY)",
"Net Income: $93.7B (-3.4% YoY)",
"EPS: $6.11 (+1.2% YoY)",
"Free Cash Flow: $111.2B",
"Share Repurchases: $77.6B"
],
"riskSummary":"34 risk factors, 12 operational, 8 financial. No new material risks.",
"recommendedActions":[
"Review Services segment growth trajectory",
"Monitor China market risk factors",
"Track capital return program sustainability"
]
},
"provenance":{
"fetchedAt":"2026-01-28T12:00:00.000Z",
"edgarUrl":"https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193",
"contentHash":"sha256:a1b2c3d4e5f6...",
"extractionVersion":"1.0.0"
},
"processingTimeMs":3456
}

Use Cases

1. AI-Powered Financial Research

Build financial research agents with grounded, citable data:

// LangChain integration
const docs = results.chunks.map(chunk=>({
pageContent: chunk.text,
metadata:{
source: results.filing.filingUrl,
ticker: results.filing.ticker,
filing_type: results.filing.filingType,
fiscal_year: results.filing.fiscalYear
}
}));
await vectorStore.addDocuments(docs);

2. Hedge Fund Due Diligence

Automate fundamental analysis across portfolio companies:

const input ={
taskMode:"full_intelligence",
tickers: portfolio.map(p=> p.ticker),
extractFinancials:true,
extractRiskFactors:true,
comparePriorYear:true
};

3. Executive Compensation Benchmarking

Compare C-suite pay across peer groups:

const input ={
taskMode:"compensation_intel",
tickers:["CRM","ORCL","SAP","WDAY","NOW"],
filingTypes:["DEF 14A"]
};

4. Risk Factor Monitoring

Track emerging risks across sectors:

const input ={
taskMode:"risk_analysis",
tickers: bankTickers,
extractRiskFactors:true,
comparePriorYear:true,
baselineRunId:"previous_run_123"
};

5. M&A Intelligence

Extract material events and strategic changes:

const input ={
taskMode:"material_events",
tickers: targetCompanies,
filingTypes:["8-K"],
dateRange:"90d"
};

Integrations

n8n Workflow

Schedule → SEC Filings Intelligence → Filter New Filings → 
 Split → [Slack Alert]+[Notion Database]+[Vector Store]

Make.com Scenario

Webhook → SEC Filings Intelligence → Router →
[Google Sheets (financials)] + [Airtable (risks)] + [Email Digest]

Direct API

curl-X POST "https://api.apify.com/v2/acts/aisolutionist~sec-filings-intelligence/runs"\
-H"Authorization: Bearer $APIFY_TOKEN"\
-H"Content-Type: application/json"\
-d'{
 "taskMode": "investor_research",
 "tickers": ["AAPL"],
 "dateRange": "1y"
 }'

SEC EDGAR Data Sources

This actor extracts from official SEC EDGAR filings:

Quality Metrics

Every extraction includes quality scores:

Pricing

Example costs:

• 10 companies × 5 filings = 50 filings → $0.01 + (50 × $0.005) = $0.26
• 100 companies × 2 filings = 200 filings → $0.01 + (200 × $0.005) = $1.01

FAQ

Q: Does this work for foreign companies? A: Yes! Form 20-F (foreign annual) and 6-K (foreign current) are supported.

Q: Can I get historical filings? A: Yes, use dateRange: "all" to access the full SEC EDGAR archive.

Q: How accurate is the financial extraction? A: We parse both HTML tables and XBRL data, cross-validating for accuracy. Quality scores indicate confidence.

Q: Do you support XBRL? A: Yes, we extract from iXBRL inline documents when available for maximum accuracy.

Q: Can I monitor for new filings? A: Schedule regular runs and use baselineRunId for change detection.

Support

• Documentation: Full API Docs
• Issues: GitHub Issues
• Contact: jason@jasonpellerin.com

License

MIT License - See LICENSE for details.

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