How to Extract Key Data from Contracts Automatically
How to Extract Key Data from Contracts Automatically
Contracts are full of critical data — parties, dates, obligations, payment terms, termination clauses — but getting that data out of a 30-page PDF and into a structured format is painful. Legal teams, procurement departments, and operations managers spend hours reading through agreements to find the key details.
Schema-based extraction changes this. Define what you want to extract, upload the contract, and get structured JSON back.
What Data Can You Extract from Contracts?
Contracts follow predictable patterns. Regardless of length or complexity, most contain:
- Parties — Who's involved, their roles, and their details
- Dates — Effective date, expiration, renewal dates
- Financial terms — Fees, payment schedules, penalties
- Obligations — What each party must do
- Termination conditions — How and when the contract can be ended
- Governing law — Which jurisdiction applies
- Key clauses — Non-compete, confidentiality, SLA terms, liability limits
Building a Contract Extraction Schema
Basic Contract Schema
For a quick overview of any agreement:
{
"type": "object",
"properties": {
"agreement_type": { "type": "string" },
"effective_date": { "type": "string", "format": "date" },
"expiration_date": { "type": "string", "format": "date" },
"parties": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": { "type": "string" },
"role": { "type": "string" },
"representative": { "type": "string" }
}
}
},
"total_value": { "type": "number" },
"currency": { "type": "string" },
"governing_law": { "type": "string" },
"summary": { "type": "string" }
}
}
Detailed Service Agreement Schema
For deeper extraction from service contracts:
{
"type": "object",
"properties": {
"agreement_number": { "type": "string" },
"agreement_type": { "type": "string" },
"effective_date": { "type": "string", "format": "date" },
"parties": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": { "type": "string" },
"role": { "type": "string" },
"registration_number": { "type": "string" },
"address": { "type": "string" },
"representative": {
"type": "object",
"properties": {
"name": { "type": "string" },
"title": { "type": "string" }
}
}
}
}
},
"term": {
"type": "object",
"properties": {
"duration_months": { "type": "integer" },
"auto_renewal": { "type": "boolean" },
"renewal_term_months": { "type": "integer" },
"notice_period_days": { "type": "integer" }
}
},
"compensation": {
"type": "object",
"properties": {
"amount": { "type": "number" },
"currency": { "type": "string" },
"frequency": { "type": "string" },
"payment_terms": { "type": "string" }
}
},
"sla": {
"type": "object",
"properties": {
"uptime_guarantee": { "type": "number" },
"response_time": { "type": "string" },
"penalty_provisions": { "type": "string" }
}
},
"termination": {
"type": "object",
"properties": {
"for_cause_notice_days": { "type": "integer" },
"for_convenience_notice_days": { "type": "integer" },
"cure_period_days": { "type": "integer" }
}
},
"confidentiality": {
"type": "object",
"properties": {
"duration_years": { "type": "integer" },
"scope": { "type": "string" }
}
},
"governing_law": { "type": "string" },
"key_obligations": {
"type": "array",
"items": { "type": "string" }
}
}
}
Example: Extracting a Service Agreement
Upload a service contract:
curl -X POST https://api.smole.tech/api/pipeline/file \
-H "Authorization: Bearer YOUR_API_KEY" \
-F "file=@service-agreement.pdf" \
-F "schemaId=SCHEMA_ID"
Get back structured data:
{
"agreement_number": "SA-2025-0847",
"agreement_type": "Managed Services Agreement",
"effective_date": "2025-06-01",
"parties": [
{
"name": "CloudOps Solutions GmbH",
"role": "Provider",
"registration_number": "HRB 198234",
"address": "Leopoldstr. 21, 80802 Munich",
"representative": { "name": "Dr. Lisa Weber", "title": "CEO" }
},
{
"name": "RetailTech AG",
"role": "Client",
"registration_number": "HRB 214567",
"address": "Kurfürstendamm 45, 10707 Berlin",
"representative": { "name": "Marc Richter", "title": "CTO" }
}
],
"term": {
"duration_months": 36,
"auto_renewal": true,
"renewal_term_months": 12,
"notice_period_days": 90
},
"compensation": {
"amount": 18500,
"currency": "EUR",
"frequency": "monthly",
"payment_terms": "Net 30"
},
"sla": {
"uptime_guarantee": 99.95,
"response_time": "1 hour for critical, 4 hours for high, 1 business day for normal",
"penalty_provisions": "10% monthly fee credit per 0.01% below SLA target"
},
"termination": {
"for_cause_notice_days": 30,
"for_convenience_notice_days": 90,
"cure_period_days": 30
},
"confidentiality": {
"duration_years": 5,
"scope": "All proprietary technical and business information"
},
"governing_law": "Federal Republic of Germany",
"key_obligations": [
"Provider shall deliver managed infrastructure services per Exhibit A",
"Provider guarantees 99.95% uptime for production systems",
"Client shall provide access credentials and documentation within 5 business days",
"Both parties shall maintain confidentiality for 5 years post-termination"
]
}
Use Cases for Contract Extraction
Contract Management
Build a searchable database of all your agreements. Know at a glance which contracts are expiring, what your total commitments are, and which vendors have specific terms.
Compliance and Audit
Extract key clauses for compliance reviews. Quickly identify all contracts with specific governing law, data processing terms, or liability provisions.
Procurement
Compare vendor contracts side by side. Extract pricing, SLA terms, and payment conditions from multiple proposals to make informed decisions.
Due Diligence
During M&A or investment processes, extract key terms from dozens or hundreds of contracts. What are the total liabilities? Which contracts have change-of-control provisions?
Handling Different Contract Types
The same approach works for:
- Employment contracts — Salary, benefits, non-compete, notice period
- NDAs — Parties, scope, duration, exceptions
- Lease agreements — Rent, term, renewal options, maintenance obligations
- License agreements — Scope, territory, exclusivity, royalties
- Partnership agreements — Profit sharing, responsibilities, dissolution terms
Just adjust your schema to match the data you need from each type.
Tips for Better Contract Extraction
- Focus on the data you'll actually use — Don't try to extract everything. Start with the fields that drive your workflow.
- Use nested objects for related data — Group party details, financial terms, and termination conditions into objects for cleaner output.
- Include a
key_obligationsarray — This catches the most important commitments from the agreement in a summarized form. - Test with your actual contracts — Every organization's contracts have slightly different patterns. Test your schema against real examples.
Try It Now
Upload a contract in the Playground and see what gets extracted. No signup needed to try it.
For API integration details, see the documentation.
Related articles
How to Extract Tables from PDFs into Structured Data
Extract tables from PDF documents into structured JSON or CSV. Handle multi-column layouts, merged cells, and inconsistent formatting with schema-based extraction.
pythonExtract Structured Data from Documents with Python
How to extract structured JSON data from PDFs, scanned documents, and Word files using Python. Complete code examples with requests, error handling, and batch processing.
ocrHow to Extract Data from Scanned Documents
Learn how to extract structured data from scanned PDFs, photographed documents, and image-based files using OCR and schema-based extraction.
