Extract KPIs from Global Filings
Find relevant company documents and transform them into normalized, backtesting-ready datasets across any region.
The challenge
A global quant firm wanted to collect historical commodity data from over 400 companies, such as web pages, CSVs, PDFs, charts, tables.
How Kadoa solves it
Automated ingestion of newly published reports
Eliminated manual data cleaning and reconciliation
Accurate extraction of key KPIs across a wide variety of reports
Normalized time series data across all sources
Data standardization
95% automated
vs. manual mapping
Data prep time
85% reduction
Across all filing types
Time to insight
Minutes
Per filing, down from hours
Kadoa
Scrape dataMonitor
Source
SEC EDGAR
10-K, 10-Q, 8-K, DEF 14A, S-1
Earnings Transcripts
Call transcripts and presentations
International Filings
Global regulatory documents
Actions
Extract
Tables, metrics, and text analysis
Normalize
Units, regions, timeframes
Destinations
Research Platform
Direct model integration
Extracted data
| Company | Commodity | Operation | Production | Unit | Period |
|---|---|---|---|---|---|
| FreePort-McMoRan | Copper Concentrate | Bagdad Mine | 47.2 | kt | Q1 2024 |
| Southern Copper | Copper (SX-EW) | La Caridad | 23.8 | kt contained | Q1 2024 |
| Antofagasta | Copper Concentrate | Los Pelambres | 89.1 | kt payable | Q1 2024 |
| BHP | Copper Concentrate | Escondida (57.5%) | 201.3 | kt | Q1 2024 |
| Glencore | Zinc Concentrate | Mount Isa | 124.6 | kt contained | Q1 2024 |
"Kadoa extracts consistent, normalized datasets from thousands of documents. What took weeks of manual processing now happens automatically."
— Head of Quantitative Research, Quant Fund
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