> ## Documentation Index
> Fetch the complete documentation index at: https://docs.aifano.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Contract Analysis

> Parse contracts, extract key clauses, dates, parties, and obligations using Aifano.

## 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.

## 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)

## Step 1: Parse the Contract

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

<CodeGroup>
  ```python Python theme={null}
  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']}")
  ```

  ```javascript JavaScript theme={null}
  const AIFANO_API_KEY = "ak_live_your_key_here";
  const BASE_URL = "https://platform.aifano.com";

  const parseResult = await fetch(`${BASE_URL}/parse`, {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${AIFANO_API_KEY}`,
      "Content-Type": "application/json"
    },
    body: JSON.stringify({ input: "aifano://service-agreement.pdf" })
  }).then(r => r.json());

  parseResult.result.chunks.forEach(chunk => {
    chunk.blocks
      .filter(b => ["Title", "Section Header"].includes(b.type))
      .forEach(b => console.log(`  [${b.type}] ${b.content}`));
  });
  ```
</CodeGroup>

## Step 2: Extract Key Contract Data

Use the job reference from Step 1 to extract structured data without re-parsing:

```python Python theme={null}
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))
```

## Step 3: Example Output

```json theme={null}
{
  "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"
}
```

## Step 4: Split Multi-Section Contracts

For contracts with multiple sections (e.g., MSA + SOW + NDA), use Split first:

```python Python theme={null}
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']})")
```

## Tips

<AccordionGroup>
  <Accordion title="Use jobid:// to save credits">
    Parse once, then extract multiple times with different schemas using `jobid://`. This avoids re-parsing and saves 1 credit per page each time.
  </Accordion>

  <Accordion title="Be specific in your schema descriptions">
    Add `description` fields to guide extraction. For example, specify date formats, currency expectations, or what constitutes a "termination clause."
  </Accordion>

  <Accordion title="Combine Split + Extract for bundled contracts">
    Split the document first to identify sections, then extract from each section individually for more accurate results.
  </Accordion>
</AccordionGroup>

## Next Steps

* [Invoice Processing](/cookbooks/invoice-processing) — Extract financial data from invoices
* [Multi-Document Pipelines](/cookbooks/multi-document-pipelines) — Build automated document workflows