How to Automate Contract Analysis with AI: A Step-by-Step Tutorial

Legal contracts are dense, time-consuming, and unforgiving. A single missed clause can expose your business to liability, delay a deal, or create compliance headaches down the road. The good news is that AI contract review has matured to the point where you can reliably automate contract analysis and extract meaningful data from legal documents in seconds — not hours.

In this tutorial, we’ll walk through how to use the Today’s World AI API to build a practical contract analysis pipeline. Whether you’re a developer building a legal tech product, an ops team tired of manual review, or a solo founder trying to move faster, this guide will show you exactly how to get started.

Why Automate Contract Analysis?

Before diving into the code, it’s worth understanding what you’re actually gaining by automating this process.

Manual contract review is slow. A typical contract lawyer spends anywhere from 30 minutes to several hours reviewing a single agreement. When you’re processing dozens or hundreds of contracts per month — vendor agreements, NDAs, employment contracts, SaaS terms — that time compounds fast.

Beyond speed, consistency is the bigger win. Human reviewers get tired. They miss things. An AI model will apply the same logic to the first contract and the thousandth. That reliability is especially valuable for:

Flagging non-standard clauses (e.g., auto-renewal terms, indemnification carve-outs)
Extracting key dates, parties, and obligations for your CRM or contract database
Identifying missing clauses that should be present in a standard agreement
Generating summaries for stakeholders who don’t need to read the full document

If you’ve read our post on “How to Extract Invoice Data from PDFs Using AI”, you’ll recognize a similar pattern here — structured data extraction from unstructured documents. Contracts are just a more complex version of that problem.

What the Today’s World AI Contract Analysis API Does

The Today’s World AI API provides a dedicated endpoint for legal document automation. You send it a contract (as raw text or a base64-encoded PDF), specify what you want extracted, and receive a structured JSON response.

Key capabilities include:

Contract clause extraction API: Pull out specific clauses by type — liability, termination, payment terms, governing law, and more
Party and date identification: Automatically detect signatories, effective dates, and expiration dates
Risk scoring: Get a simple risk flag on clauses that deviate from standard language
Summary generation: Receive a plain-English summary of the entire document

You can explore the full capabilities in the API documentation.

Setting Up Your Environment

You’ll need:

An API key from Today’s World AI — get started with a free tier that includes enough credits to test on real documents
A sample contract in plain text or PDF format
A terminal (for curl examples) or any HTTP client in your preferred language

For this tutorial, we’ll use curl to keep things simple and language-agnostic.

Step 1: Extract Key Clauses from a Contract

The most common use case is contract clause extraction — pulling out specific sections so you don’t have to read the whole document. Here’s how to call the API:

curl -X POST https://api.todaysworld.com/v1/contracts/analyze \
  -H "Content-Type: application/json" \
  -H "x-api-key: YOUR_API_KEY" \
  -d '{
    "document_text": "This Service Agreement is entered into as of January 1, 2025, between Acme Corp (\"Client\") and Vendor LLC (\"Provider\"). ... [full contract text here] ...",
    "extract": ["parties", "effective_date", "termination_clause", "payment_terms", "liability_cap", "governing_law"],
    "risk_analysis": true,
    "summary": true,
    "document_type": "service_agreement"
  }'

Understanding the Request Body

document_text: The full text of the contract. If you’re working with PDFs, see the next step for how to handle binary files.
extract: An array of clause types you want the API to identify and return. You can request as many or as few as needed.
risk_analysis: When set to true, each extracted clause receives a risk flag (low, medium, or high) based on deviation from standard language.
summary: Set to true to receive a plain-English executive summary.
document_type: Optional but improves accuracy. Accepted values include nda, service_agreement, employment_contract, sow, and lease.

Sample Response

{
  "document_type": "service_agreement",
  "parties": {
    "client": "Acme Corp",
    "provider": "Vendor LLC"
  },
  "effective_date": "2025-01-01",
  "clauses": {
    "termination_clause": {
      "text": "Either party may terminate this agreement with 30 days written notice...",
      "risk": "low"
    },
    "liability_cap": {
      "text": "Provider's total liability shall not exceed the fees paid in the prior 30 days...",
      "risk": "high",
      "risk_reason": "Liability cap is unusually short at 30 days; standard is 12 months."
    },
    "governing_law": {
      "text": "This agreement shall be governed by the laws of Delaware.",
      "risk": "low"
    }
  },
  "summary": "A service agreement between Acme Corp and Vendor LLC effective January 1, 2025. Notable concern: liability cap limited to 30-day fee window, which is below market standard."
}

The response gives you clean, structured contract data extraction you can immediately push into a database, trigger a review workflow, or surface to a business stakeholder.

Step 2: Analyze a PDF Contract Directly

Most real-world contracts come as PDFs. The API accepts base64-encoded files so you can send the document without needing a file hosting step.

curl -X POST https://api.todaysworld.com/v1/contracts/analyze \
  -H "Content-Type: application/json" \
  -H "x-api-key: YOUR_API_KEY" \
  -d '{
    "document_base64": "JVBERi0xLjQKJcOkw7zDtsOfCjIgMCBvYmoK...",
    "document_format": "pdf",
    "extract": ["parties", "effective_date", "payment_terms", "auto_renewal", "termination_clause"],
    "risk_analysis": true,
    "summary": true
  }'

In practice, you’d base64-encode your file programmatically. In Python, for example:

import base64

with open("contract.pdf", "rb") as f:
    encoded = base64.b64encode(f.read()).decode("utf-8")

Then insert that string as the value of document_base64. For full code examples in Python, Node.js, and PHP, check the API docs.

Step 3: Build a Basic Review Pipeline

Once you can call the API, the next step is wiring it into a workflow. Here’s a practical pipeline for a team that receives vendor contracts via email:

Ingest: Email parser (e.g., Zapier, n8n, or a custom webhook) detects a new contract attachment and extracts the PDF
Analyze: Send the PDF to the /v1/contracts/analyze endpoint with your standard clause list
Route: If any clause returns risk: high, flag the contract for human legal review; otherwise, approve automatically
Store: Push extracted fields (parties, dates, payment terms) into your CRM or contract management system
Notify: Send a Slack or email summary to the relevant stakeholder

This kind of legal document automation doesn’t replace your legal team — it filters what actually needs their attention so they spend time on real problems instead of routine extraction.

Step 4: Customize Clause Extraction for Your Use Case

The API supports custom clause queries beyond the preset list. If you have domain-specific language you need to track — say, data processing addendums for GDPR compliance, or specific SLA thresholds — you can pass a custom_extract array:

curl -X POST https://api.todaysworld.com/v1/contracts/analyze \
  -H "Content-Type: application/json" \
  -H "x-api-key: YOUR_API_KEY" \
  -d '{
    "document_text": "... [contract text] ...",
    "custom_extract": [
      "data processing obligations",
      "SLA uptime guarantee",
      "source code escrow"
    ],
    "risk_analysis": false
  }'

The model will search for language matching those concepts and return the relevant text, even if it doesn’t map to a standard clause name.

Tips for Better Results

Clean your text: If converting from PDF to text yourself, watch for OCR artifacts. The API handles most cases, but cleaner input means cleaner output.
Be specific with document_type: Even if you’re not sure of the exact type, passing your best guess improves clause detection accuracy.
Batch processing: For high-volume workflows, use the /v1/contracts/batch endpoint (documented in the API docs) to submit multiple contracts in a single request.
Compare to a baseline: If you have a standard contract template, you can submit both the template and an incoming contract and ask the API to highlight differences. This is especially useful for AI contract review of redlined documents.

If you’re also processing financial documents alongside contracts, our post “Parse Receipts Automatically with AI API” covers a similar extraction pattern that pairs well with this workflow.

Practical Limitations to Keep in Mind

No tool is perfect. A few things worth noting:

Very long contracts (100+ pages) may need to be chunked into sections before submission, depending on your plan’s token limits
Handwritten or scanned contracts with poor image quality will reduce extraction accuracy
Jurisdiction-specific nuances: The risk scoring is based on general commercial contract standards — always have a qualified attorney review high-stakes agreements

Summary

Automating contract analysis with AI is one of the higher-leverage things you can do if your business deals with legal documents regularly. With a few API calls, you can go from a dense PDF to structured, actionable contract data — parties, dates, clauses, and risk flags — without writing complex NLP logic yourself.

The Today’s World AI API makes this accessible through a clean REST interface, whether you’re building a full legal tech product or just trying to stop copying data from contracts into a spreadsheet by hand.

Ready to automate your workflow? Try it free at todaysworld.com/try or get API access on RapidAPI.