SEC EDGAR Intel

TL;DR for hedge fund analysts, fintech teams, and due-diligence teams: Classifies SEC filings (8-K material events, Form 4 insider clusters, 13F QoQ position deltas, Form D startup raises, going-concern, 8-K Exhibit 99 earnings transcripts) directly off the free SEC EDGAR APIs. Compared to the raw SEC EDGAR API or a sec_edgar_downloader script, you get pre-classified intelligence (event_type, confidence, evidence_text on every 8-K, cluster-buy flags on every Form 4, QoQ delta on every 13F) plus an MCP-ready sibling actor for agents. Free Apify plan covers exploration runs on your $5 platform credit. PPE charges per filing plus enrichment. Upgrade to Apify Starter ($49/mo) for production volume.

Run it in 30 seconds

# Via the Apify Python SDK
from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("seibs.co/sec-edgar-intel").call(run_input={
    "mode": "company_filings",
    "tickers": [
        "AAPL"
    ],
    "date_from": "2026-04-01",
    "user_agent_contact": "you@example.com"
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

Or via curl:

curl -X POST "https://api.apify.com/v2/acts/seibs.co~sec-edgar-intel/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"mode": "company_filings", "tickers": ["AAPL"], "date_from": "2026-04-01", "user_agent_contact": "you@example.com"}'

Or click "Try for free" on this page if you prefer the no-code UI.

What you get

Each run produces:

• A clean dataset, filterable in the Apify console and downloadable as CSV or JSON
• An OUTPUT.html dashboard preview of your top records
• A sample-output preview at ./.actor/sample-output.json

Per-archetype custom artifacts shipped with this actor:

• filings.csv (pre-classified with event_type, confidence, evidence_text)
• form4-clusters.csv (insider Form 4 trades with cluster-buy and unusual-size flags)
• 13f-deltas.csv (manager position changes quarter-over-quarter)

---

What does SEC EDGAR Intel do?

It hits the free public SEC EDGAR APIs (data.sec.gov + www.sec.gov/cgi-bin/browse-edgar) and post-processes every filing into pre-classified intelligence: 8-K material events, Form 4 cluster-buy / unusual-size flags, 13F quarter-over-quarter position deltas, Form D startup raises, going-concern detection on 10-K/10-Q risk factors, and 8-K Exhibit 99.x earnings transcript extraction.

AI / RAG / Agent

A turn-key LLM feed for hedge-fund research bots, fintech RAG, and due-diligence agents. Filings arrive pre-classified (event_type, confidence, evidence_text) so an agent can filter on mergers_acquisitions or going_concern without reading the raw 8-K. Earnings transcripts are chunked by speaker turn and ready to embed. Compatible with LangChain, LlamaIndex, Pinecone, Weaviate, Chroma, and any MCP-aware agent runtime.

from apify_client import ApifyClient
from langchain.schema import Document
from langchain_community.vectorstores import Weaviate
from langchain_openai import OpenAIEmbeddings

client = ApifyClient("APIFY_TOKEN")
run = client.actor("you/sec-edgar-intel").call(run_input={
    "mode": "earnings_transcripts",
    "tickers": ["NVDA", "MSFT", "AAPL"],
    "lookbackDays": 90,
})

docs = [
    Document(
        page_content=turn["text"],
        metadata={
            "ticker": item["ticker"],
            "cik": item["cik"],
            "filing_date": item["filing_date"],
            "speaker": turn.get("speaker"),
            "role": turn.get("role"),
            "form_type": item["form_type"],
        },
    )
    for item in client.dataset(run["defaultDatasetId"]).iterate_items()
    for turn in item.get("transcript_turns", [])
]

Weaviate.from_documents(docs, OpenAIEmbeddings(), index_name="EdgarEarnings")

Features

• 8-K material event classifier - mergers_acquisitions, executive_change, going_concern, impairment, class_action, restatement, dividend_change, debt_issuance, customer_loss, bankruptcy, auditor_change, restructuring and more, with confidence scores and text evidence.
• Form 4 insider pattern flags - cluster_buy, unusual_size, c_suite_only, post_10b5_1_termination.
• 13F position change tracker - new / increased / decreased / exited / unchanged per holding, with share-count delta and percentage.
• Going-concern detector for 10-K / 10-Q risk sections with evidence excerpts.
• Form D startup raise tracker - total offering, amount sold, investor count, related persons.
• Earnings transcript extraction from 8-K Exhibit 99.1 / 99.2.
• Full-text search across the EDGAR full-text index (filings since 2001) with keyword excerpts.
• SEC fair-access compliance - required User-Agent input + 8 req/sec semaphore.

Use cases

• Hedge funds and quant teams - daily Form 4 cluster-buy alerts, 13F position changes the day they hit EDGAR.
• Fintech apps - pre-classified 8-K events drive push notifications without running internal NLP.
• Due diligence and M&A - going-concern detection across portfolios; restatement / auditor change scanning.
• Securities litigation - class action and restatement detection across an industry.
• Journalists - bulk Form D scraping for startup raise scoops.
• VC analysts - Form D funding tracker with investor and related-persons extraction.

FAQ

Q: Is this legal? A: Yes. EDGAR is the SEC's public filing system. Every record this actor pulls is mandated-public by federal securities law. No login, no paywall, no scraping of restricted data.

Q: How is this different from the 30+ other EDGAR actors on Apify? A: Most EDGAR actors are raw-download utilities - they hand you the filing index or the raw XBRL and call it done. This actor is an intelligence layer on top: (1) 8-K filings come pre-classified by trigger event - acquisition, executive departure, restatement, bankruptcy, auditor change, going-concern, material agreement - so you can route by event type without writing classifiers, (2) Form 4 filings come with cluster-buy detection - the actor flags coordinated insider purchases across multiple officers/directors within a rolling window, the single highest-signal insider-trading pattern, (3) 13F filings come with quarter-over-quarter position deltas already computed - new positions, exits, increased / decreased holdings, with $ impact, (4) Form D filings come with investor lists and related-persons extracted into flat fields ready for CRM ingest, (5) full-text search returns excerpt snippets, not just hit URLs. You skip the parsing layer entirely.

Q: Why might a run fail? A: The two most common failure modes are (1) SEC EDGAR rate-limiting if your User-Agent header doesn't comply with the SEC's fair-access policy (the actor handles this automatically), and (2) requesting a CIK / ticker that EDGAR doesn't recognize - always pass tickers in uppercase and CIKs zero-padded to 10 digits or as plain integers.

Q: How fresh is the data? A: EDGAR publishes filings within seconds of acceptance. The actor pulls live at run time, so latency from filing-acceptance to actor-output is typically under 60 seconds. 8-K filings are particularly time-sensitive - most material-event 8-Ks must be filed within 4 business days, but many hit EDGAR within hours.

Q: Can I schedule this daily or weekly? A: Yes. Daily cron is appropriate for 8-K monitoring, Form 4 cluster-buy alerts, and Form D fundraising trackers. Quarterly cron is appropriate for 13F position-delta runs (13Fs are filed within 45 days of quarter-end). Apify Schedules + dedupe on accession_number gives a clean delta feed.

Q: Does it integrate with my CRM or data tooling? A: Yes. Apify webhooks POST every run to HubSpot, Salesforce, Pipedrive, Apollo, Slack, or any HTTP endpoint. Zapier, Make.com, and n8n templates available. Dataset exports as JSON / CSV / Excel / XML for downstream BI tools.

Q: How does pricing work? A: PAY_PER_EVENT. You pay per filing record emitted, with surcharges on the high-signal events (cluster-buy detections, classified 8-K triggers, 13F position deltas). You only pay for what the actor actually emits.

Related Actors

• us-gov-contracts-intel - federal contract awards for the same public companies you're tracking on EDGAR.
• court-records-intel - pull every PACER / federal court case for the same entities to surface securities litigation, going-concern triggers, and IP / contract disputes.
• b2b-sales-triggers - convert EDGAR events (acquisitions, executive departures, fundraising) into outbound sales triggers for your AE / SDR team.

Integrations

• Zapier - push to HubSpot/Salesforce/Pipedrive/Apollo
• Make.com - workflow automation
• n8n - self-hosted automation
• Apify webhooks - POST to your endpoint
• API + dataset export (JSON/CSV/Excel/XML)
• MCP / AI agents - call from Claude/GPT/LangChain

Modes

Mode	What it returns
company_filings	All filings for the given tickers/CIKs, filtered by form type and date range.
recent_8k	Most recent 8-K filings + trigger classification + earnings transcripts when present.
form_4_insider	Form 4 insider trades with reporter, role, transactions, and pattern flags.
form_d_funding	Form D startup raises with offering amounts, investors, and related persons.
13f_positions	13F-HR institutional holdings with quarter-over-quarter position changes.
full_text_search	Keyword search across EDGAR full-text with excerpt snippets.

Input

See .actor/INPUT_SCHEMA.json for the full input form. Key fields:

{
    "mode": "recent_8k",
    "tickers": ["AAPL", "MSFT"],
    "form_types": ["8-K"],
    "date_from": "2026-01-01",
    "include_8k_trigger_classification": true,
    "user_agent_contact": "MyApp contact@example.com",
    "max_results_per_query": 100
}

user_agent_contact is required - SEC fair-access policy demands an identifying email; misidentified requests get IP-banned.

Output

Sample output: ./.actor/sample-output.json â€" copy-paste-ready preview of real-looking records.

First record inline:

{
  "cik": "0001318605",
  "ticker": "ASPN",
  "company_name": "Aspen Aerogels, Inc.",
  "sic": "2899",
  "sic_industry": "INDUSTRIAL & MISCELLANEOUS CHEMICALS",
  "exchange": "NYSE",
  "form_type": "8-K",
  "accession_number": "0001318605-26-000048",
  "filing_date": "2026-05-09",
  "period_of_report": "2026-05-09",
  "filing_url": "https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0001318605&type=8-K",
  "primary_document_url": "https://www.sec.gov/Archives/edgar/data/1318605/000131860526000048/aspn-20260509.htm",
  "scraped_at": "2026-05-13T20:14:08Z",
  "mode": "form_8k_triggers",
  "available": true,
  "reason": null,
  "item_codes": [
    "1.01",
    "5.02"
  ],
  "trigger_classification": {
    "categories": [
      "material_definitive_agreement",
      "executive_change"
    ],
    "confidence": {
      "material_definitive_agreement": 0.92,
      "executive_change": 0.88
    },
    "evidence": {
      "material_definitive_agreement": [
        "entered into a Master Supply Agreement with"
      ],
      "executive_change": [
        "resignation of John Q. Smith, Chief Financial Officer",
        "appointment of Maya Lindgren as interim CFO"
      ]
    }
  },
  "reporter_name": null,
  "role": null,
  "transactions": null,
  "unusual_size_flag": null,
  "cluster_buy_flag": null,
  "c_suite_only_flag": null,
  "post_10b5_1_termination_flag": null,
  "total_offering_amount": null,
  "amount_sold": null,
  "investors_count": null,
  "first_sale_date": null,
  "related_persons": null,
  "holdings": null,
  "risk_factors_summary": null,
  "going_concern_detected": null,
  "going_concern_evidence": null,
  "executive_compensation_summary": null,
  "business_section_summary": null,
  "earnings_transcript_detected": false,
  "earnings_transcript_text": null,
  "matched_excerpts": null,
  "full_text": null
}

One dataset record per filing. Sample:

{
    "cik": "0000320193",
    "ticker": "AAPL",
    "company_name": "Apple Inc.",
    "form_type": "8-K",
    "accession_number": "0001193125-26-012345",
    "filing_date": "2026-04-30",
    "filing_url": "https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193",
    "item_codes": ["2.02", "9.01"],
    "trigger_classification": {
        "categories": ["earnings", "dividend_change"],
        "confidence": {"earnings": 0.92, "dividend_change": 0.71}
    },
    "earnings_transcript_detected": true,
    "scraped_at": "2026-05-14T12:00:00Z",
    "available": true,
    "mode": "recent_8k"
}

Failed lookups still emit a record with available: false and a reason for completeness audit.

Pricing

Pay-per-event:

Event	Price	When charged
filing_record	$0.005	Per filing returned with metadata.
intelligence_enrichment	$0.010	When a trigger classification, Form 4 pattern flag, or going-concern signal is detected.
full_text_charge	$0.015	When include_full_text=true and raw filing text is embedded.
earnings_transcript_charge	$0.010	When an earnings transcript is extracted from 8-K Exhibit 99.x.

A typical 100-filing recent_8k run with classification on costs roughly $0.50 - $1.50.

FAQ

Q: Do I need an SEC API key? A: No - SEC EDGAR is fully public. You only need to set user_agent_contact to an identifying email so SEC can reach you if your usage misbehaves.

Q: Will it get my account IP-banned? A: Not if you keep concurrency at or below 8 (the default is 6) and provide an honest user_agent_contact. The actor self-throttles to stay below SEC's 10 req/sec cap.

Q: How far back does data go? A: Submissions JSON returns the most recent ~1000 filings per CIK. Run multiple date-windowed queries for deeper history. Full-text search covers filings since 2001.

Q: How accurate is the 8-K trigger classifier? A: It maps Item codes (1.01, 5.02, 4.02, etc.) and runs keyword regex clusters with confidence scores plus evidence snippets. Spot-check before using for compliance work.

Save your input as an Apify Task

Apify Tasks let you save a configured input once and re-run it with a single click - no need to re-type search terms, locations, filters, or tier settings every time. Tasks are the foundation for everything that comes next: schedules, monitor mode, and webhook routing all attach to a saved Task, not to the raw actor.

Steps to save your current input as a Task:

1. On this actor's Apify Store page, click Run with your input fully configured.
2. Click the Save as task button at the top of the run page.
3. Name the task something memorable (e.g. 8-K filings for watchlist - daily).
4. Reload the task page and click Start anytime to re-run with the same inputs.

Tasks unlock the next two features below: scheduling and monitor mode.

Run this weekly with Apify Schedules

Apify Schedules cron-run any saved Task automatically. Pair this with the saved Task above and you get hands-off recurring runs with no manual clicks, no missed weeks, and a steady stream of fresh data into your CRM or warehouse.

Steps to schedule a Task:

1. Save your input as a Task (see above).
2. Go to https://console.apify.com/schedules and click Create new schedule.
3. Pick your Task and set the cron expression. Common patterns:
   • Daily at 9am UTC: 0 9 * * *
   • Weekly on Mondays at 9am: 0 9 * * 1
   • Monthly on the 1st: 0 9 1 * *
4. Save. Apify will run your Task on that schedule automatically, push the dataset to whatever integrations you have wired up, and fire run-completion webhooks for downstream automation.

Run daily to monitor for new filings, material events, and insider transactions across the tickers you track.

Monitor mode (v2, beta)

Monitor mode is the v2 evolution of this actor and is currently in BETA. It turns a recurring schedule into a true change-feed instead of a firehose of duplicate records.

How it works:

• When this actor runs under an Apify Schedule, monitor mode is enabled automatically.
• Instead of emitting ALL records every run, it emits ONLY records that are NEW or CHANGED since the last scheduled run.
• A digest record summarizes the delta (X new, Y changed, Z removed) at the top of every run.
• Optional: provide a Slack or email webhook URL in the monitor_webhook_url input field and the digest fires there too, so your team gets the delta in their inbox or channel without polling the dataset.
• Cost: a single scheduled_delta_run event ($0.05) per scheduled run, plus standard PPE on emitted delta records only. Predictable monthly cost, no surprise bills from re-charging for unchanged records.

Monitor mode is rolling out to the top 3 actors first (this one included if it's hotel-motel-lead-finder, google-maps-reviews-pro, or mcp-accounting-firm-leads). Full portfolio coverage by end of June.

Support

Open an issue on the actor's GitHub or email the maintainer via the Apify Store contact link. Include the run ID and the input config so the issue is reproducible.

Changelog

See ./CHANGELOG.md.

Found this useful?

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