Metadata-Version: 2.4
Name: enrich-companies
Version: 0.1.0
Summary: Enrich a CSV of companies with revenue, employees, credit score & financial data from 250M+ business records
Author-email: Alessandro Binda <ale@get-scala.com>
License: MIT
Project-URL: Homepage, https://github.com/Alessandro114/enrich-companies
Project-URL: Repository, https://github.com/Alessandro114/enrich-companies
Project-URL: Bug Tracker, https://github.com/Alessandro114/enrich-companies/issues
Project-URL: Score API, https://score.get-scala.com
Keywords: company-data,csv,enrichment,business-intelligence,lead-enrichment,financial-data,revenue,employees,credit-score,eu-companies,company-lookup,sales-intelligence,data-enrichment,b2b,company-database
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Office/Business
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Dynamic: license-file

# enrich-companies

Enrich a CSV of company names with revenue, employees, credit score, and financial data from **250M+ business records** across 50+ countries.

**Zero dependencies. Zero config. Just works.**

```bash
pip install enrich-companies
enrich-companies companies.csv -o enriched.csv
```

## What it does

You give it a CSV with company names. It gives you back the same CSV with 16 extra columns:

| Added Column | Example |
|---|---|
| `revenue` | 12500000 |
| `employees` | 340 |
| `health_score` | 78.5 |
| `nace_code` | 56.10 |
| `nace_description` | Restaurants |
| `legal_form` | S.r.l. |
| `status` | active |
| `city` | Milan |
| `country` | IT |
| `vat_number` | IT12345678901 |
| `founded` | 2015-03-12 |
| `website` | example.com |
| `phone` | +39 02 1234567 |
| `email` | info@example.com |
| `postal_code` | 20121 |
| `score_id` | abc123 |

## Install

```bash
pip install enrich-companies
```

No API key needed. Free tier: 50 lookups/month.

## Usage

### Basic

```bash
enrich-companies input.csv -o output.csv
```

### Auto-detect columns

The tool auto-detects columns named `company`, `company_name`, `name`, `business_name`, `organization`, `firma`, `empresa`, `azienda`, etc.

### Specify columns

```bash
enrich-companies input.csv -o output.csv --name-col "Company Name" --country-col "Country"
```

### Semicolon-separated (European CSVs)

```bash
enrich-companies input.csv -o output.csv --delimiter ";"
```

### Pipe to stdout

```bash
enrich-companies input.csv | head -5
```

## Example

**Input (`companies.csv`):**
```csv
company_name,country
Ferrero,IT
Siemens,DE
LVMH,FR
```

**Run:**
```bash
enrich-companies companies.csv -o enriched.csv
```

**Output:**
```
  Enriching 3 companies from companies.csv...

  [1/3] Ferrero — Revenue: 17000000000 | Employees: 41000 | Score: 92
  [2/3] Siemens — Revenue: 72000000000 | Employees: 311000 | Score: 88
  [3/3] LVMH — Revenue: 86000000000 | Employees: 213000 | Score: 95

  Done! 3/3 companies enriched
  Output: enriched.csv
```

## Data coverage

- **250M+ companies** across 50+ countries
- Strong coverage: IT, DE, FR, ES, UK, NL, BE, AT, CH, CZ, PL, RO, US, and more
- Sources: official business registries, financial filings, public records
- Updated regularly

## Also available

- **Node.js/npm**: `npx enrich-companies companies.csv` — [enrich-companies on npm](https://www.npmjs.com/package/enrich-companies)
- **Python SDK**: `pip install scala-score` — [scala-score on PyPI](https://pypi.org/project/scala-score/)
- **MCP Server**: `scala-mcp-server` — let AI agents search company data
- **Chrome Extension**: [Score Company Lookup](https://chromewebstore.google.com/detail/score-company-lookup/)
- **Dataset**: [250M companies on Kaggle](https://www.kaggle.com/datasets/alessandrobinda/european-company-database) | [HuggingFace](https://huggingface.co/datasets/Alessandro114/european-company-database)

## License

MIT
