Real Estate Use Case

How real estate professionals use Archivus for property documents, transaction management, and client portals.

Overview

Real estate professionals handle property documents: contracts, inspections, disclosures, transaction records. Archivus helps real estate teams:

  • Property documents - Organize documents by property
  • Transaction management - Track documents through transactions
  • Client portals - Share documents securely with clients
  • Compliance - Manage disclosure requirements and retention

Key Use Cases

Property Document Management

Challenge: Organizing documents for multiple properties and transactions.

Solution: Use folders to organize by property:

from archivus import ArchivusClient

client = ArchivusClient(api_key="YOUR_API_KEY", tenant="real-estate")

# Create property folder structure
properties_folder = client.folders.create("Properties", color="#3B82F6")

# Create property-specific folder
property_123 = client.folders.create(
    "123 Main St",
    parent_id=properties_folder.id,
    color="#10B981"
)

# Upload property documents
documents = [
    "purchase-agreement.pdf",
    "inspection-report.pdf",
    "disclosure-statement.pdf",
    "title-report.pdf",
    "appraisal.pdf"
]

for doc in documents:
    client.documents.upload(
        doc,
        folder_id=property_123.id,
        enable_ai=True,
        tags=["property_123_main_st", "transaction_2025", "active"]
    )

Benefits:

  • Property organization - All documents in one place
  • Easy access - Find documents quickly
  • Transaction tracking - Tag documents by transaction

Transaction Management

Challenge: Tracking documents through the transaction process.

Solution: Use tags and search to track transaction status:

# Tag documents by transaction stage
transaction_stages = [
    "offer",
    "inspection",
    "appraisal",
    "closing",
    "completed"
]

# Upload and tag documents
for stage in transaction_stages:
    docs = client.search.search(
        query=f"documents for {stage} stage",
        mode="semantic",
        tag_id=f"tag_{stage}"
    )
    
    print(f"{stage.capitalize()} Stage: {len(docs['results'])} documents")

# Find documents needing attention
pending_docs = client.search.search(
    query="documents pending review or signature",
    mode="semantic",
    tag_id="tag_pending"
)

# Track transaction progress
transaction_docs = client.search.search(
    query="all documents for transaction 2025-001",
    mode="semantic",
    tag_id="tag_transaction_2025_001"
)

Benefits:

  • Status tracking - See transaction progress at a glance
  • Pending items - Find documents needing attention
  • Complete history - All transaction documents in one place

Client Portal

Challenge: Sharing documents securely with clients.

Solution: Use share links and workspaces:

# Create client workspace
client_workspace = client.workspaces.create(
    "Smith Family - Property Purchase",
    description="Documents for 123 Main St purchase"
)

# Upload documents to workspace
property_docs = [
    "purchase-agreement.pdf",
    "inspection-report.pdf",
    "disclosure-statement.pdf"
]

for doc in property_docs:
    client.documents.upload(
        doc,
        workspace_id=client_workspace.id
    )

# Create shareable link for client
share_link = client.documents.create_share_link(
    document_id="doc_purchase_agreement",
    permission="view",
    expires_days=30,
    password="client-secure-password"
)

print(f"Share this link with client: {share_link['share_link']}")

Benefits:

  • Secure sharing - Password-protected, time-limited links
  • Client access - Clients can view documents easily
  • Professional - Clean, branded client portal

Document Analysis

Challenge: Quickly understanding key terms in contracts and agreements.

Solution: Use AI chat to analyze documents:

# Upload purchase agreement
agreement = client.documents.upload("purchase-agreement.pdf")

# Analyze agreement
session = client.chat.create_session(agreement.id, "Agreement Analysis")

questions = [
    "What is the purchase price?",
    "What is the closing date?",
    "What are the contingencies?",
    "What are the inspection requirements?",
    "Are there any special terms or conditions?"
]

for question in questions:
    response = client.chat.ask(session.id, question)
    print(f"Q: {question}")
    print(f"A: {response.content}\n")

Benefits:

  • Quick analysis - Understand contracts instantly
  • Key terms - Extract important information
  • Risk identification - Identify potential issues

Real-World Example

Real Estate Agency: Premier Properties

Challenge:

  • Managing 100+ active transactions
  • Organizing documents for 50+ properties
  • Sharing documents with clients securely
  • Tracking transaction deadlines

Solution with Archivus:

  • Created folder for each property
  • Tagged documents by transaction and stage
  • Created client workspaces for each transaction
  • Used AI to analyze contracts and agreements

Results:

  • 80% faster document organization
  • 90% faster client document sharing
  • 100% compliance with disclosure requirements
  • Improved client satisfaction with faster responses

Essential

  • Document upload and organization
  • Folder structure for properties
  • Secure client sharing
  • Semantic search
  • Workspace collaboration
  • Share links with expiration
  • Document analysis with AI
  • Transaction tracking

Advanced

  • Custom AI agents for real estate workflows
  • Integration with MLS systems
  • Advanced analytics and reporting
  • Client portal customization

Pricing

Real estate professionals typically use:

  • Starter Plan ($55 CAD/month) - For individual agents
  • Pro Plan ($99 CAD/month) - For small teams
  • Team Plan ($249 CAD/month) - For larger agencies

Next Steps

Questions? Contact support@ubiship.com or sales@ubiship.com