> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cerevox.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Legal Research
> Transform legal document analysis with AI-powered parsing and precise extraction
# Legal Document Analysis with Lexa
Revolutionize legal research and document review with Lexa's enterprise-grade document parsing. Extract precise information from contracts, case files, and legal documents with unmatched accuracy.
## Why Lexa for Legal Practice?
Extract clauses, terms, and citations with 99.5% accuracy
SOC 2 certified with attorney-client privilege protection
Analyze complex contracts and legal agreements
Process thousands of discovery documents efficiently
## Supported Legal Documents
* **Contracts & Agreements** (MSAs, NDAs, employment agreements)
* **Court Filings** (pleadings, motions, briefs)
* **Discovery Documents** (depositions, exhibits, correspondence)
* **Case Law** (judicial opinions, legal precedents)
* **Regulatory Filings** (SEC forms, compliance documents)
* **Legal Research** (law journals, legal treatises)
* **Patent Applications** and intellectual property documents
## Quick Start: Contract Analysis
Extract key terms and clauses from legal contracts:
```python Contract Analysis theme={null}
from cerevox import Lexa
# Initialize client
client = Lexa(api_key="your-api-key")
# Parse legal contract
documents = client.parse("service_agreement.pdf")
contract = documents[0]
# Extract key contract terms
liability_clauses = contract.search_content("liability|indemnif")
termination_terms = contract.search_content("termination|expire")
payment_terms = contract.search_content("payment|fee|invoice")
print(f"Contract: {contract.filename}")
print(f"Pages: {contract.total_pages}")
print(f"Liability clauses: {len(liability_clauses)}")
print(f"Payment terms: {len(payment_terms)}")
```
```python Async Batch Processing theme={null}
import asyncio
from cerevox import AsyncLexa
async def analyze_contract_portfolio():
async with AsyncLexa(api_key="your-api-key") as client:
# Process multiple contracts
contracts = [
"msa_template.pdf",
"nda_standard.docx",
"employment_agreement.pdf"
]
documents = await client.parse(contracts)
contract_analysis = []
for doc in documents:
analysis = {
'filename': doc.filename,
'pages': doc.total_pages,
'key_terms': extract_legal_terms(doc),
'risk_clauses': doc.search_content("risk|liable|penalty"),
'obligations': doc.search_content("shall|must|required")
}
contract_analysis.append(analysis)
return contract_analysis
def extract_legal_terms(document):
"""Extract common legal terms"""
terms = [
"confidential", "proprietary", "intellectual property",
"termination", "breach", "indemnification", "liability"
]
found_terms = {}
for term in terms:
matches = document.search_content(term)
found_terms[term] = len(matches)
return found_terms
# Run analysis
results = asyncio.run(analyze_contract_portfolio())
```
## Advanced Legal Analysis
### Contract Clause Extraction
Build a comprehensive contract analysis system:
```python theme={null}
from cerevox import AsyncLexa
import re
from typing import Dict, List
class ContractAnalyzer:
def __init__(self, api_key: str):
self.client = AsyncLexa(api_key=api_key)
# Define clause patterns
self.clause_patterns = {
'termination': [
r'terminat[e|ion].*?(?:\.|;|\n)',
r'end.*?agreement.*?(?:\.|;|\n)'
],
'liability': [
r'liabilit.*?(?:\.|;|\n)',
r'indemnif.*?(?:\.|;|\n)'
],
'confidentiality': [
r'confidential.*?(?:\.|;|\n)',
r'proprietary.*?(?:\.|;|\n)'
]
}
async def analyze_contract(self, contract_path: str) -> Dict:
"""Comprehensive contract analysis"""
async with self.client:
documents = await self.client.parse(contract_path)
contract = documents[0]
analysis = {
'contract_info': {
'filename': contract.filename,
'pages': contract.total_pages
},
'extracted_clauses': {},
'risk_assessment': self._assess_risks(contract)
}
# Extract clauses by type
for clause_type, patterns in self.clause_patterns.items():
clauses = []
for pattern in patterns:
matches = re.findall(pattern, contract.content, re.IGNORECASE)
clauses.extend(matches)
analysis['extracted_clauses'][clause_type] = {
'count': len(clauses),
'text': clauses[:3] # First 3 matches
}
return analysis
def _assess_risks(self, contract) -> Dict:
"""Assess legal risks in contract"""
high_risk_terms = [
"unlimited liability", "personal guarantee",
"liquidated damages", "penalty"
]
risks = {}
for term in high_risk_terms:
matches = contract.search_content(term)
if matches:
risks[term] = {
'count': len(matches),
'severity': 'high'
}
return risks
# Usage
analyzer = ContractAnalyzer("your-api-key")
analysis = await analyzer.analyze_contract("service_agreement.pdf")
```
### Legal Document Search & RAG
Build a legal research system with semantic search:
```python theme={null}
from cerevox import AsyncLexa
from typing import List, Dict
class LegalRAGSystem:
def __init__(self, api_key: str):
self.client = AsyncLexa(api_key=api_key)
self.legal_corpus = []
async def ingest_legal_documents(self, document_paths: List[str]):
"""Ingest legal documents for search"""
async with self.client:
documents = await self.client.parse(document_paths)
# Create searchable chunks optimized for legal content
for doc in documents:
chunks = doc.get_text_chunks(
target_size=800, # Good for legal context
tolerance=0.2
)
for i, chunk in enumerate(chunks):
self.legal_corpus.append({
'id': f"{doc.filename}_{i}",
'content': chunk,
'document': doc.filename,
'document_type': self._classify_document(doc.filename)
})
return f"Ingested {len(self.legal_corpus)} legal document chunks"
def search_legal_precedents(self, query: str, limit: int = 5) -> List[Dict]:
"""Search for legal precedents and relevant cases"""
results = []
query_terms = query.lower().split()
for chunk in self.legal_corpus:
content_lower = chunk['content'].lower()
# Score based on term frequency
score = sum(1 for term in query_terms if term in content_lower)
if score > 0:
results.append({
'content': chunk['content'],
'document': chunk['document'],
'relevance_score': score,
'document_type': chunk['document_type']
})
# Sort by relevance and return top results
results.sort(key=lambda x: x['relevance_score'], reverse=True)
return results[:limit]
def _classify_document(self, filename: str) -> str:
"""Classify legal document type"""
filename_lower = filename.lower()
if any(term in filename_lower for term in ['contract', 'agreement']):
return 'contract'
elif any(term in filename_lower for term in ['case', 'opinion']):
return 'case_law'
elif any(term in filename_lower for term in ['brief', 'motion']):
return 'court_filing'
else:
return 'legal_document'
# Usage
legal_rag = LegalRAGSystem("your-api-key")
await legal_rag.ingest_legal_documents(["contracts.pdf", "case_law.pdf"])
results = legal_rag.search_legal_precedents("intellectual property")
```
## Real-World Legal Use Cases
### Due Diligence Automation
```python theme={null}
async def automated_due_diligence(target_company_docs):
"""Automate due diligence document review"""
async with AsyncLexa(api_key="your-api-key") as client:
documents = await client.parse(target_company_docs)
due_diligence_report = {}
for doc in documents:
# Extract critical information
due_diligence_report[doc.filename] = {
'contract_terms': doc.search_content("term|clause|provision"),
'liabilities': doc.search_content("liabilit|debt|obligation"),
'intellectual_property': doc.search_content("patent|trademark"),
'litigation_risks': doc.search_content("lawsuit|litigation"),
'compliance_issues': doc.search_content("regulation|compliance")
}
return due_diligence_report
```
### Discovery Document Processing
```python theme={null}
async def process_discovery_documents(document_list: List[str]):
"""Process large volumes of discovery documents"""
async with AsyncLexa(api_key="your-api-key") as client:
BATCH_SIZE = 10
all_results = {}
for i in range(0, len(document_list), BATCH_SIZE):
batch = document_list[i:i + BATCH_SIZE]
documents = await client.parse(batch)
for doc in documents:
key_info = {
'pages': doc.total_pages,
'communications': doc.search_content("email|letter|memo"),
'privileged_content': doc.search_content("attorney|counsel"),
'key_people': extract_people_names(doc)
}
all_results[doc.filename] = key_info
return all_results
```
## Performance for Legal Documents
**45 seconds** for 500+ page legal brief
**99.5%** accuracy on contract clauses
**1000+ documents/hour** batch processing
## Security & Compliance
Attorney-client privilege and work product protection maintained throughout processing
* **Privileged Content**: Automatic detection and protection
* **Data Isolation**: Client data never shared or used for training
* **Audit Trail**: Complete processing logs for compliance
* **Access Controls**: Role-based access with detailed permissions
## Next Steps
Start processing legal documents in minutes
Explore legal-specific parsing methods
Learn production patterns for legal workflows
Understand our security measures