Programmatic Regulatory Alpha
We don't build generic dashboards for fundamental analysts. We build sub-100ms WebSocket firehoses and point-in-time correct historical datasets mapping European MAR 19 insider transactions, TED tenders, and lobbying meetings directly to tradable ISINs.
5,000 point-in-time defense procurement notices mapped to parent tickers
// Example WebSocket Payload - Revolving Door Alert
{
"event_type": "entity_resolution_match",
"timestamp": "2026-08-07T12:00:01.421Z",
"data": {
"entity_name": "TechLobbying Partners GmbH",
"matched_individual": {
"name": "Klaus Schmidt",
"former_role": "MEP (DE)",
"committee": "IMCO (Internal Market)",
"resignation_date": "2026-03-15"
},
"confidence_score": 0.98,
"active_dossiers": ["AI Act Implementation", "Digital Markets Act"]
},
"latency_ms": 14
}Structured Policy Datasets
Explore exactly how our normalized datasets map directly to algorithmic trading strategies.
Available Data Feeds
Corporate Entities
Use this mapping layer to resolve messy European public data to standard identifiers like LEIs, ISINs, and tickers, enabling clean programmatic joins across our entire data suite.
{
"id": "CORP-8F932",
"name": "Siemens AG",
"sector": "Industrials",
"headquarters_country": "DE",
"identifiers": {
"lei": "529900CJPO2OQQ242X05",
"ticker": "SIE.DE"
}
}Entity Resolution Engine
Messy EU registers output strings like "Airbus Operations GmbH". Legacy providers force you to clean this. We do it upstream. Our graph database maps 24,000+ localized corporate variations directly to standard LEIs and traded tickers (AIR.PA).
Point-In-Time Correctness
Backtesting against terminal data is deeply flawed due to retroactive corrections. Our historical dumps include `published_at` and `revised_at` timestamps. Test your models against what was actually known at T-zero, avoiding look-ahead bias entirely.
Sub-100ms Delivery
When a major public tender is awarded on TED, or an insider trade is declared on BaFin, you shouldn't have to poll an API. We push the structured JSON payload to your webhook within 100ms of it hitting the public domain.
Backtesting EU Defense Procurement Tender Spikes vs SXPARO Equities
Run this full Python research notebook directly in your browser. Demonstrates upstream subsidiary entity resolution, 30-day tender momentum z-scores, and zero look-ahead bias execution against the STOXX Europe Aerospace & Defense benchmark.
# 1. Ingest Point-in-Time 5-Year Defense Procurement Sample
import pandas as pd
import numpy as np
url = "https://altdataeu.com/samples/eu_defense_procurement_5yr_sample.csv"
df = pd.read_csv(url)
# Parse point-in-time publication timestamps
df['point_in_time_publication_date'] = pd.to_datetime(df['point_in_time_publication_date'])
df['award_date'] = pd.to_datetime(df['award_date'])
# Upstream Entity Resolution: Notice subsidiary resolution to parent tickers
print(f"Total Tenders: {len(df):,} | Date Range: {df['award_date'].min().date()} to {df['award_date'].max().date()}")
print(df[['tender_id', 'buyer_country', 'awarded_vendor_raw', 'parent_ticker', 'parent_isin', 'contract_value_eur']].head(5))
# Output:
# tender_id buyer_country awarded_vendor_raw parent_ticker parent_isin contract_value_eur
# 0 TED-2021-0000 UK Kongsberg Maritime AS KOG.OL NO0003043309 117,180,000.0
# 1 TED-2021-0001 DE Airbus CyberSecurity SAS AIR.PA NL0000235190 21,190,000.0
# 2 TED-2021-0002 NO Kongsberg Maritime AS KOG.OL NO0003043309 12,030,000.0
# 3 TED-2021-0003 SE Hensoldt Sensors GmbH HAG.DE DE000HAG0005 10,460,000.0
# 4 TED-2021-0004 FR Thales Ground Transportation SAS HO.PA FR0000121329 43,330,000.0API Endpoints & Data Dictionary
Full technical coverage across all 27 member states and EU institutions.
| Feed Type | Latency | Historical Depth | Primary Analysis Use Case |
|---|---|---|---|
| Public Procurement (TED) | sub-100ms | 2014 - Present | Revenue forecasting, unannounced defense contracts |
| Lobbying Registers | Real-time sync | 2008 - Present | Regulatory risk, upcoming legislative roadblocks |
| Insider Trading (BaFin/AMF) | sub-150ms | 2010 - Present | Directors' dealings correlated with lobbying velocity |
| Legislative Velocity | Daily EOD | 1999 - Present | Macro sector rotation based on regulatory drag |
Test the Firehose (No Sales Call)
Drop your work email below. You'll instantly receive a 7-day, rate-limited trial key to pull live data. We'll only follow up after you've had a chance to test it.