Alt-Data

What's inside#

• Workforce. A monthly employment panel per company (headcount, hiring and attrition rates, average salary) and US WARN-Act layoff filings, which employers must file weeks before a cut. Two cross-sectional screens rank who is hiring and who is filing layoff notices.
• Supply chain. The relationship graph around a company (customers, suppliers, competitors and partners, from 2003 on), two-sided revenue dependence, and estimated revenue by region and country for each fiscal period.
• Governance and accounting quality. Board size and independence, director interlocks, restatement record, auditor changes and executive pay in one dossier, and graded forensic red flags with the evidence rows attached.
• Political and government exposure. Quarterly lobbying spend and federal contract awards per company, the awards as quarterly totals rather than individual contracts (2,318 tickers covered), plus a cross-ticker contracts feed.
• Innovation, pay and retail attention. USPTO patents tagged to a company, annual executive compensation, and daily r/wallstreetbets mentions and sentiment with up to 365 days of history.

Other licensed-research datasets bill as Alt-Data but are documented with their families: point-in-time financials on Fundamentals, the identifier crosswalk on Reference Data, insider flow split by 10b5-1 plans, Form 144 notices, current top shareholders and the licensed 13F dataset (/api/v3/ownership/*) on Funds & Institutional, and the macro history (/api/v3/macro_history/*) and estimates history (/api/v3/estimates_history/*) on Macro, Rates & FX.

Access#

Endpoints#

Workforce#

Workforce caveats.

• Headcount, flows and salary are modelled vendor estimates, not company-reported figures. units in each response says what every field measures.
• The panel's newest month can sit well behind today: in August 2026 the panel held 2024-01 to 2024-10. Before treating a figure as current, read coverage.panel_last_month, and on momentum_screen read from_month and to_month, which are the two panel months being compared, not today and an earlier month.
• The monthly panel is still being backfilled. Every response carries a coverage block with the months held, supported_lookback_months, trailing_12m_available and yoy_available. A growth figure the loaded window cannot support comes back as value_pct: null with a reason, never interpolated; a months_back the screen cannot support returns warning: "lookback_not_loaded" with available_months_back.
• Coverage leans to large companies. coverage.universe_coverage reports the live share of the tradable universe the panel reaches and coverage.coverage_by_market_cap breaks it down by size.
• A ticker is not unique across venues. The symbol is resolved to a security first and the employer matched on its identifiers.
  • warning: "ambiguous_symbol" with candidates means more than one current security shares the symbol. Re-ask with an unambiguous identifier.
  • When no employer can be proven to be the resolved company, the call is refused with a warning such as no_identity_matched_employer, identity_unverifiable_ambiguous_panel (identity_unverifiable_ambiguous_filings on layoffs) or identity_not_proven_string_match_only. The employers filed under that symbol are listed in symbol_collisions, with identity fields only and no figures.
  • A served answer also lists any other employers under the same string in symbol_collisions.
  • To read one of those employers, pass its employer_id. If its identity still cannot be proven, the figures come back under unverified_employer_figures rather than latest or momentum, and identity_verified is false.
• Layoff filings are site-level, so one restructuring appears as many rows: read employees_affected_total, not the row count. Coverage is US WARN notices from 1989, including forward-dated notices. Only employers matched to a listed symbol are reachable, so an empty result is not proof there were no layoffs.
• The screen's state filter matches the filed spelling exactly. A value that matches no filing returns a warning (state_case_mismatch with did_you_mean, or state_not_a_filed_value with filed_states) instead of an empty result.

Supply chain and geographic revenue#

Supply-chain caveats.

• revenue_percent is always a share of the source company's revenue, and revenue_percent_of_ticker names whose revenue it is, so the number is never read backwards. Every value is a vendor estimate, and only a minority of relationships carry one: a missing percent means unknown, never zero. disclosed_revenue_pct_total is a floor on customer concentration and does not add to 100.
• History is not yet point-in-time. A relationship's knowledge date is its start date, but the vendor records relationships retroactively, so history can claim a relationship was known years before it reached the feed (median about six years). Current relationships are correct. New pulls are stamped when fetched from 2026-09-27; older history will be restated.
• The default view is current relationships only; most history is closed. Pass status=all or as_of= for history, and group_by=record to see every underlying record.
• Geographic layers each sum to 100 on their own, so never add a region to a country. Amounts carry no currency code and the reporting currency can change between periods: compare on percent. These are estimates, not company-reported segments; for reported segments use /api/v3/fundamentals/segments/{ticker} on Fundamentals.
• The symbol is resolved to a security and the vendor matched on its own identifiers. A security the vendor does not carry (often an ADR, whose local line has different identifiers) returns warning: "not_covered_by_vendor" with the identifiers tried. A symbol shared by more than one current security is refused with warning: "ambiguous_symbol". When several vendor companies match equally well, the call is refused with warning: "ambiguous_vendor_company" and the matches in candidates; pass company_id to pick one. On a served answer, alternates lists other companies that matched only on a weaker identifier. They are listed, not served.

Governance and accounting quality#

The flags accounting_flags can raise:

Governance evidence is filed per issuer. If the ticker cannot be pinned to one SEC CIK, accounting_flags returns error: "cik_not_linked" with an empty flags list rather than guessing, and the dossier's restatement and auditor blocks say the same.

Political and government exposure#

Innovation, pay and retail attention#

Warehouse copies and refusals. lobbying, gov_contracts and patents read a warehouse copy of the alternative-data feed first, and the live feed only for a ticker the copy does not hold. A warehouse answer has source: "warehouse:<product>-archive" and its own clocks: as_of and archive_ingested_at (when the copy last carried the rows), data_through (the newest item date, or for contracts the newest snapshot), data_from (the oldest item held for the ticker), history_floor (where the copy begins for every ticker) and a coverage_note. Records dated before data_from or history_floor may exist at the source and are not included, so do not describe the answer as the complete history.

When neither the copy nor the live feed can answer, these routes, and exec_compensation, wsb and gov_contracts_live, return 503 with error: "upstream_unavailable" instead of an empty list, not billed. The body has no items field. error_code says why: upstream_dead_no_archive (the live feed failed and no copy holds the ticker, Retry-After: 900), archive_read_timeout (the copy's read ran out of time and keeps running, so a retry in about a minute is usually served; Retry-After: 60), archive_read_failed (Retry-After: 120) or build_busy (the read was not started; Retry-After: 30). A 503 means the data could not be retrieved, not that the company has no lobbying, contracts or patents.

Examples#

Example 1: Lobbying spend (bash)#

curl -H "Authorization: Bearer $WEALTHNOW_API_KEY" \  "https://firm.wealthnow.io/api/v3/intel/lobbying/AAPL?limit=20" # Response:# {#   "ok": true,#   "timestamp": "2026-09-24T14:22:00Z",#   "ticker": "AAPL",#   "items": [#     {#       "ticker": "AAPL",#       "client": "Apple Inc.",#       "amount": 2330000.0,#       "issue": "...",#       "date": "2026-07-18"#     },#     ...#   ],#   "count": 20# }

Example 2: Government contracts (Python)#

import os, requests r = requests.get(    "https://firm.wealthnow.io/api/v3/intel/gov_contracts/MSFT",    headers={"Authorization": f"Bearer {os.environ['WEALTHNOW_API_KEY']}"},    params={"limit": 10},    timeout=30,)r.raise_for_status()data = r.json()  # envelope: {"ok": true, "timestamp": ..., "ticker": "MSFT", "items": [...], "count": N, "granularity": "quarterly_total", "source": "..."}contracts = data["items"]print(f"Latest {len(contracts)} quarters of contract awards for MSFT")for contract in contracts[:3]:    print(f"  {contract['year']}Q{contract['quarter']}: ${contract['amount']:,.0f}")

Example 3: Is a company hiring or shrinking? (bash)#

curl -H "Authorization: Bearer $WEALTHNOW_API_KEY" \  "https://firm.wealthnow.io/api/v3/workforce/momentum/NVDA?months=12" # Response (abridged):# {#   "ok": true,#   "timestamp": "2026-09-24T14:30:00Z",#   "company": "NVIDIA Corp",#   "employer_id": 123456,#   "identity_verified": true,#   "identity_match": {"matched_on": "CUSIP9", "grain": "security", ...},#   "coverage": {"supported_lookback_months": [1, 2, 3, ...], "trailing_12m_available": false, "yoy_available": false, ...},#   "latest": {"month": "2024-10", "headcount": 36120.4, "hires": 612.0, "departures": 301.5, "net_change": 310.5, "salary_avg_usd": 198000, ...},#   "momentum": {#     "available": true,#     "as_of_month": "2024-10",#     "headcount": 36120.4,#     "hiring_rate_pct_per_month": 1.694,#     "attrition_rate_pct_per_month": 0.835,#     "net_hiring_rate_pct_per_month": 0.86,#     "hire_to_departure_ratio": 2.03,#     "headcount_growth_3m": {"value_pct": 2.412, "from_month": "2024-07", "to_month": "2024-10", ...},#     "headcount_growth_12m": {"value_pct": null, "reason": "no_panel_month:2023-10", "from_month": "2023-10"},#     "direction": "expanding"#   },#   "history": [...],#   "units": {...},#   "source": "warehouse:workforce-panel"# }

headcount_growth_12m is null with a reason because the panel does not hold that month yet; it is never estimated. The newest month here is 2024-10, not last month: check coverage.panel_last_month before reading the result as current.

Example 4: Who filed layoff notices this quarter (Python)#

import os, requests r = requests.get(    "https://firm.wealthnow.io/api/v3/workforce/layoff_screen",    params={"days": 90, "min_employees": 500, "limit": 25},    headers={"Authorization": f"Bearer {os.environ['WEALTHNOW_API_KEY']}"},    timeout=60,)r.raise_for_status()data = r.json()# {#   "ok": true,#   "window": {"since": "2026-06-26", "days": 90},#   "filters": {"min_employees": 500, "state": null},#   "n_companies": 25,#   "truncated": true,#   "companies": [#     {"ticker": "...", "employer_id": ..., "company": "...", "isin": "...", "n_filings": 14,#      "employees_affected": 2310, "largest_filing_employees": 640,#      "first_event_date": "2026-07-02", "latest_event_date": "2026-09-30", "n_states": 5},#     ...#   ],#   "source": "warehouse:layoff-filings"# }for c in data["companies"]:    # Join on employer_id / isin, not on the ticker string: a symbol can belong to several employers.    print(c["ticker"], c["company"], c["employees_affected"], "employees across", c["n_filings"], "filings")

Example 5: Customers, suppliers and who depends on them (bash)#

curl -H "Authorization: Bearer $WEALTHNOW_API_KEY" \  "https://firm.wealthnow.io/api/v3/supply_chain/relationships/AAPL?rel_type=suppliers&limit=10" # Response (abridged):# {#   "ok": true,#   "ticker": "AAPL",#   "company": "Apple Inc.",#   "company_id": "...",#   "status": "current",#   "counts": {#     "suppliers": {"n_records": 441, "n_counterparties": 402, "n_reported_by_company": 24,#                   "n_reported_by_counterparty": 417, "n_returned": 10, "truncated": true,#                   "n_with_revenue_percent": 51, "revenue_percent_coverage_pct": 11.56}#   },#   "relationships": {#     "suppliers": [#       {"counterparty": "Cirrus Logic Inc.", "counterparty_ticker": "CRUS", "counterparty_is_listed": true,#        "role": "supplier", "is_current": true, "reported_from": ["counterparty"],#        "revenue_percent": 89.0, "revenue_percent_of_ticker": "CRUS",#        "revenue_percent_of_company": "Cirrus Logic Inc.", "revenue_percent_estimated": true, ...},#       ...#     ]#   },#   ...# }

Here revenue_percent: 89.0 is 89% of Cirrus Logic's revenue coming from Apple, not the reverse.

Example 6: How much revenue comes from China and Taiwan (Python)#

import os, requests r = requests.get(    "https://firm.wealthnow.io/api/v3/supply_chain/geo_revenue/NVDA",    params={"country": "CN,TW", "top_countries": 10},    headers={"Authorization": f"Bearer {os.environ['WEALTHNOW_API_KEY']}"},    timeout=60,)r.raise_for_status()geo = r.json()# geo["period"]        -> {"period_end_date": "2026-01-25", "period_start_date": "2025-01-27", "mode": "latest_available"}# geo["countries"]     -> [{"region": "United States", "iso_alpha_2": "US", "revenue_percent": 44.1,#                           "confidence": 0.82, "certainty_class": "...", ...}, ...]# geo["concentration"] -> {"largest_country": "United States", "largest_country_pct": 44.1, "country_hhi": 0.27, ...}# geo["country_history"] -> per-period exposure to exactly CN and TWfor row in geo["countries"]:    print(f"{row['region']:<20} {row['revenue_percent']:>6.2f}%  (confidence {row['confidence']})")

Example 7: Forensic accounting flags (bash)#

curl -H "Authorization: Bearer $WEALTHNOW_API_KEY" \  "https://firm.wealthnow.io/api/v3/intel/accounting_flags/SMCI?limit=10" # Response (abridged):# {#   "ok": true,#   "ticker": "SMCI",#   "cik": "...",#   "n_flags": 3,#   "flags": [#     {"flag": "auditor_resigned", "severity": "high",#      "reason": "auditor RESIGNED 1 time(s); auditors walking away is a classic precursor of accounting trouble"},#     ...#   ],#   "restatements": {"n": ..., "rows": [...]},#   "auditor_changes": {"n": ..., "rows": [...]},#   "audit_fees_by_year": [...],#   "identity_verified": true,#   "grain": "issuer",#   "source": "warehouse:forensic-audit-archive"# }

Related#