If you've ever tried to extract data from invoices, receipts, or bank statements in PDF format, you know how painful it is.
OCR tools often return messy text, and regex rules quickly break when document layouts change. You end up spending more time cleaning data than using it.
That's why I built AIxtract — an AI-powered PDF Data Extractor API that uses Claude AI to intelligently detect, classify, and extract structured information from documents.
Traditional PDF parsers just read text. AIxtract understands documents.
| Feature | Description |
|---|---|
| 🧾 Automatic Document Detection | Detects invoices, payslips, bank statements, and contracts |
| 📊 Smart Table Extraction | Extracts rows, headers, and totals into clean JSON |
| 🌍 Multilingual Support | Works with 50+ languages |
| ⚡ Fast & Reliable | Average 3–5s per document |
| 🔒 Secure | Files deleted within 24h, GDPR compliant |
It combines FastAPI performance, Claude 3.5 Sonnet reasoning, and traditional PDF parsing tools to produce structured, high-confidence data.
You can test the API instantly on RapidAPI.
Here's a quick example in Python:
import requests
url = "https://aixtract2.p.rapidapi.com/extract"
headers = {
"x-rapidapi-key": "YOUR_RAPIDAPI_KEY",
"x-rapidapi-host": "aixtract2.p.rapidapi.com"
}
files = {"file": open("invoice.pdf", "rb")}
data = {"use_ai": "true", "extract_tables": "true"}
response = requests.post(url, headers=headers, files=files, data=data)
print(response.json()){
"document_type": "invoice",
"structured_data": {
"invoice_number": "INV-2024-001",
"invoice_date": "2024-03-15",
"supplier_name": "ACME Corp",
"total_ttc": 1250.00
},
"tables": [
{
"headers": ["Description", "Quantity", "Price", "Total"],
"rows": [
["Consulting", "10", "100", "1000"]
]
}
],
"confidence_score": 0.95
}In just a few seconds, the API classifies your document and gives you structured JSON data ready for integration.
Here's how developers and companies are already using AIxtract:
Automatically extract invoice numbers, totals, and line items to feed into your accounting system.
Turn PDF statements into transaction data for financial dashboards or reconciliation apps.
Extract salary, deductions, and employee data for HR automation.
Parse parties, dates, and key terms from legal documents.
You can plug AIxtract into any workflow:
- Python / Node.js / PHP / Ruby SDK examples in the docs
- Works with Zapier, Make (Integromat), or custom pipelines
- Webhooks (coming soon) for async processing
Docs: https://api.aixtract.xyz/docs
| Plan | Requests/month | Price | Description |
|---|---|---|---|
| 🎁 Free | 50 | $0 | Great for testing and prototyping |
| ⭐ Pro | 500 | $9.99 | Ideal for freelancers and startups |
| 🚀 Ultra | 1000 | $29 | Best for businesses and integrations |
All plans include AI extraction, table parsing, and multilingual support.
👉 Start free now at AIxtract.xyz
✅ RESTful API built on FastAPI
🧠 Claude AI 3.5 Sonnet for structured extraction
📦 Multiple SDKs (Python, JS, PHP, Ruby)
🕒 3–5s average processing
📉 Confidence score for every document
🔒 GDPR compliant – files deleted after 24h
- 🧾 Invoice Automation Tool – Parse PDF invoices and sync with QuickBooks
- 💼 Finance Dashboard – Visualize bank transactions in real time
- 🧠 AI Document Assistant – Chat with extracted PDF data
- 🗂️ Bulk Document Parser – Process 1000+ PDFs in minutes
If you build something cool with it, I'd love to feature your project on the AIxtract site.
AIxtract is actively evolving:
- Webhook notifications (coming soon)
- Asynchronous processing for large PDFs
- Template-based field extraction
- ERP integrations (Xero, SAP, QuickBooks)
- Smart analytics & anomaly detection
You can follow updates via the RapidAPI page or join the upcoming Discord community.
AIxtract exists because developers shouldn't have to waste time scraping PDFs.
If your workflow involves invoices, statements, or receipts, give AIxtract a try — it might save you hours of manual parsing.
- 🚀 Try it free today → https://aixtract.xyz
- 📡 API on RapidAPI → AI PDF Data Extractor
- 🧠 Docs → https://api.aixtract.xyz/docs