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Overview

This cookbook demonstrates how to analyze contracts using Aifano’s Parse and Extract endpoints. You’ll learn to extract parties, dates, key clauses, and obligations from legal documents — turning dense PDFs into structured, queryable data.

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What You’ll Build

A workflow that:
  1. Parses a contract into structured sections
  2. Extracts key metadata (parties, dates, terms)
  3. Identifies specific clauses (termination, liability, confidentiality)

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Step 1: Parse the Contract

First, parse the contract to get the full text with section structure: 
import requests

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

# Parse the contract
parse_result = requests.post(
    f"{BASE_URL}/parse",
    headers={"Authorization": f"Bearer {AIFANO_API_KEY}"},
    json={"input": "aifano://service-agreement.pdf"}
).json()

# Print section headers
for chunk in parse_result["result"]["chunks"]:
    for block in chunk["blocks"]:
        if block["type"] in ("Title", "Section Header"):
            print(f"  [{block['type']}] {block['content']}")

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Step 2: Extract Key Contract Data

Use the job reference from Step 1 to extract structured data without re-parsing:
Python
schema = {
    "type": "object",
    "properties": {
        "contract_title": {"type": "string"},
        "effective_date": {"type": "string", "description": "YYYY-MM-DD format"},
        "expiration_date": {"type": "string", "description": "YYYY-MM-DD format"},
        "parties": {
            "type": "array",
            "items": {
                "type": "object",
                "properties": {
                    "name": {"type": "string"},
                    "role": {"type": "string", "description": "e.g., Client, Provider, Vendor"},
                    "address": {"type": "string"}
                }
            }
        },
        "contract_value": {"type": "number", "description": "Total contract value"},
        "currency": {"type": "string"},
        "payment_terms": {"type": "string"},
        "termination_clause": {"type": "string", "description": "Summary of termination conditions"},
        "liability_cap": {"type": "string", "description": "Maximum liability amount or terms"},
        "confidentiality": {"type": "boolean", "description": "Whether an NDA/confidentiality clause exists"},
        "governing_law": {"type": "string", "description": "Jurisdiction or governing law"},
        "renewal_terms": {"type": "string", "description": "Auto-renewal or renewal conditions"}
    }
}

# Use jobid:// to skip re-parsing (saves credits!)
job_id = parse_result["job_id"]
extract_result = requests.post(
    f"{BASE_URL}/extract",
    headers={"Authorization": f"Bearer {AIFANO_API_KEY}"},
    json={
        "input": f"jobid://{job_id}",
        "schema": schema,
        "system_prompt": "Extract all contract metadata. Summarize clauses concisely. Use YYYY-MM-DD for dates."
    }
).json()

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

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Step 3: Example Output

{
  "contract_title": "Master Service Agreement",
  "effective_date": "2024-01-01",
  "expiration_date": "2025-12-31",
  "parties": [
    { "name": "Acme Corp", "role": "Client", "address": "Berlin, Germany" },
    { "name": "TechServ GmbH", "role": "Provider", "address": "Munich, Germany" }
  ],
  "contract_value": 120000,
  "currency": "EUR",
  "payment_terms": "Net 30 days from invoice date",
  "termination_clause": "Either party may terminate with 90 days written notice. Immediate termination for material breach.",
  "liability_cap": "Limited to 12 months of fees paid",
  "confidentiality": true,
  "governing_law": "German law, courts of Berlin",
  "renewal_terms": "Auto-renews for 1-year periods unless terminated 90 days prior"
}

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Step 4: Split Multi-Section Contracts

For contracts with multiple sections (e.g., MSA + SOW + NDA), use Split first:
Python
split_result = requests.post(
    f"{BASE_URL}/split",
    headers={"Authorization": f"Bearer {AIFANO_API_KEY}"},
    json={
        "input": "aifano://contract-bundle.pdf",
        "split_description": [
            {"title": "Master Service Agreement", "description": "The main service agreement"},
            {"title": "Statement of Work", "description": "Scope, deliverables, and timeline"},
            {"title": "Non-Disclosure Agreement", "description": "Confidentiality terms"}
        ]
    }
).json()

for section in split_result["result"]:
    print(f"Section: {section['category']} (pages {section['page_range']['start']}-{section['page_range']['end']})")

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Tips

Parse once, then extract multiple times with different schemas using jobid://. This avoids re-parsing and saves 1 credit per page each time.
Add description fields to guide extraction. For example, specify date formats, currency expectations, or what constitutes a “termination clause.”
Split the document first to identify sections, then extract from each section individually for more accurate results.

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Next Steps