SEC Filings Intelligence - 10-K Decoded for AI Agents

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.

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

Mode	Description	Best For
annual_report	Full 10-K analysis	Comprehensive research
quarterly_report	10-Q extraction	Earnings tracking
material_events	8-K parsing	Breaking news, M&A
proxy_statement	DEF 14A analysis	Governance, compensation
investor_research	Balanced extraction	Due diligence
risk_analysis	Deep risk factor dive	Risk management
compensation_intel	Executive pay focus	Benchmarking
full_intelligence	Maximum extraction	Complete analysis

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:

Form	Description	Key Data
10-K	Annual Report	Full financials, risk factors, MD&A, business description
10-Q	Quarterly Report	Interim financials, updated risks, quarterly MD&A
8-K	Current Report	Material events, M&A, management changes
DEF 14A	Proxy Statement	Executive compensation, board elections, shareholder proposals
S-1	Registration	IPO prospectus, pre-IPO financials
20-F	Foreign Annual	Foreign private issuer annual report

Quality Metrics

Every extraction includes quality scores:

Metric	Description	Target
overallScore	Composite quality (0-100)	>85
financialsCompleteness	% of expected metrics found	>90
riskExtraction	Risk factor parsing accuracy	>85
compensationParsing	Exec comp table extraction	>90
citationCoverage	% with source citations	100

Pricing

Event	Price	Description
Actor Start	$0.01	Per run initialization
Filing Processed	$0.005	Per SEC filing extracted

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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