Invoice Processing

Overview

This cookbook shows how to extract structured data from invoices using the Aifano /extract endpoint. You’ll define a JSON schema for the data you need, and Aifano will extract it from any invoice format — PDF, scanned image, or digital document.

What You’ll Build

A script that:

Uploads an invoice to Aifano
Extracts vendor info, line items, totals, and payment terms
Returns clean, structured JSON ready for your accounting system

Step 1: Define the Extraction Schema

Create a JSON schema that describes the data you want to extract:

{
  "type": "object",
  "properties": {
    "invoice_number": {
      "type": "string",
      "description": "The invoice number or ID"
    },
    "invoice_date": {
      "type": "string",
      "description": "Invoice date in YYYY-MM-DD format"
    },
    "due_date": {
      "type": "string",
      "description": "Payment due date in YYYY-MM-DD format"
    },
    "vendor": {
      "type": "object",
      "properties": {
        "name": { "type": "string" },
        "address": { "type": "string" },
        "tax_id": { "type": "string" }
      }
    },
    "line_items": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "description": { "type": "string" },
          "quantity": { "type": "number" },
          "unit_price": { "type": "number" },
          "total": { "type": "number" }
        }
      }
    },
    "subtotal": { "type": "number" },
    "tax": { "type": "number" },
    "total": { "type": "number" },
    "currency": { "type": "string" }
  }
}

Step 2: Extract Data from an Invoice

import requests
import json

AIFANO_API_KEY = "ak_live_your_key_here"
BASE_URL = "https://platform.aifano.com"

# Define the extraction schema
schema = {
    "type": "object",
    "properties": {
        "invoice_number": {"type": "string", "description": "Invoice number"},
        "invoice_date": {"type": "string", "description": "Date in YYYY-MM-DD"},
        "vendor": {
            "type": "object",
            "properties": {
                "name": {"type": "string"},
                "address": {"type": "string"}
            }
        },
        "line_items": {
            "type": "array",
            "items": {
                "type": "object",
                "properties": {
                    "description": {"type": "string"},
                    "quantity": {"type": "number"},
                    "unit_price": {"type": "number"},
                    "total": {"type": "number"}
                }
            }
        },
        "subtotal": {"type": "number"},
        "tax": {"type": "number"},
        "total": {"type": "number"},
        "currency": {"type": "string"}
    }
}

# Extract data
result = requests.post(
    f"{BASE_URL}/extract",
    headers={"Authorization": f"Bearer {AIFANO_API_KEY}"},
    json={
        "input": "https://example.com/invoice.pdf",
        "schema": schema,
        "system_prompt": "Extract all invoice data. Use YYYY-MM-DD for dates. Use the document currency."
    }
).json()

print(json.dumps(result["result"], indent=2))

const AIFANO_API_KEY = "ak_live_your_key_here";
const BASE_URL = "https://platform.aifano.com";

const schema = {
  type: "object",
  properties: {
    invoice_number: { type: "string" },
    invoice_date: { type: "string" },
    vendor: {
      type: "object",
      properties: {
        name: { type: "string" },
        address: { type: "string" }
      }
    },
    line_items: {
      type: "array",
      items: {
        type: "object",
        properties: {
          description: { type: "string" },
          quantity: { type: "number" },
          unit_price: { type: "number" },
          total: { type: "number" }
        }
      }
    },
    subtotal: { type: "number" },
    tax: { type: "number" },
    total: { type: "number" },
    currency: { type: "string" }
  }
};

const result = await fetch(`${BASE_URL}/extract`, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${AIFANO_API_KEY}`,
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    input: "https://example.com/invoice.pdf",
    schema: schema,
    system_prompt: "Extract all invoice data. Use YYYY-MM-DD for dates."
  })
}).then(r => r.json());

console.log(JSON.stringify(result.result, null, 2));

curl -X POST "https://platform.aifano.com/extract" \
  -H "Authorization: Bearer ak_live_your_key_here" \
  -H "Content-Type: application/json" \
  -d '{
    "input": "https://example.com/invoice.pdf",
    "schema": {
      "type": "object",
      "properties": {
        "invoice_number": {"type": "string"},
        "vendor": {"type": "object"},
        "line_items": {"type": "array"},
        "total": {"type": "number"}
      }
    }
  }'

Step 4: Batch Processing Multiple Invoices

For processing multiple invoices, use async endpoints to maximize throughput:

Python

import time

invoice_urls = [
    "aifano://invoice-001.pdf",
    "aifano://invoice-002.pdf",
    "aifano://invoice-003.pdf",
]

# Submit all jobs
jobs = []
for url in invoice_urls:
    job = requests.post(
        f"{BASE_URL}/extract_async",
        headers={"Authorization": f"Bearer {AIFANO_API_KEY}"},
        json={"input": url, "schema": schema}
    ).json()
    jobs.append(job["job_id"])
    print(f"Submitted: {job['job_id']}")

# Poll for results
results = []
for job_id in jobs:
    while True:
        status = requests.get(
            f"{BASE_URL}/job/{job_id}",
            headers={"Authorization": f"Bearer {AIFANO_API_KEY}"}
        ).json()

        if status["status"] in ("COMPLETED", "FAILED"):
            results.append(status)
            break
        time.sleep(2)

print(f"Processed {len(results)} invoices")

Tips

Use system_prompt for better accuracy

Add context like currency format, date format, or language to the system_prompt to improve extraction accuracy.

Reuse parsed results with jobid://

If you need to extract different fields from the same invoice, use jobid:// to skip re-parsing and save credits.

Handle missing fields gracefully

Not all invoices have every field. Check for null values in the response and handle them in your application logic.

Next Steps

Contract Analysis — Extract clauses and terms from legal documents
Multi-Document Pipelines — Process bundled document packages

​Overview

​What You’ll Build

​Step 1: Define the Extraction Schema

​Step 2: Extract Data from an Invoice

​Step 4: Batch Processing Multiple Invoices

​Tips

​Next Steps