Real Estate Company: RAG Knowledge Base for €1.2B in Assets
How a real estate company managing €1.2 billion in assets reduced document search time by 60% with an internal RAG chatbot.
Context
Client name anonymized for confidentiality reasons.
This French real estate company manages a portfolio of over €1.2 billion in assets: offices, retail, logistics. Their team of 45 people (asset managers, lawyers, property managers) handles thousands of documents daily:
- Commercial leases and amendments
- Management contracts and mandates
- Urban planning regulations
- Expert reports and audits
- Tenant correspondence
The problem: an asset manager spent an average of 2h30 per day searching for information in these documents scattered between servers, emails and digitized physical archives.
The solution
We deployed an on-premise RAG knowledge base accessible via an internal web interface and integrated with their Azure AD SSO.
Key features
-
Natural language search
"What are the renewal clauses for the Carrefour lease on the Lyon Part-Dieu asset?"
-
Automatic data extraction
- Lease expiration dates
- Rent amounts and indexations
- Special clauses (works, termination, etc.)
-
Proactive alerts
- Notification 6 months before lease expiry
- Detection of unusual clauses
-
Complete audit trail
- Access traceability
- Sources cited for each response
Technical architecture
- Deployment: On-premise on client infrastructure (no data in the cloud)
- Ingestion: SharePoint connectors, emails, OCR scanner
- Security: Azure AD SSO, access logs, AES-256 encryption
- Model: Self-hosted LLM (Mistral 7B) for GDPR compliance
Results
After 6 months of deployment across all teams:
| Metric | Before | After | Change |
|---|---|---|---|
| Search time/day | 2h30 | 1h | -60% |
| Data entry errors | 12/month | 2/month | -83% |
| Tenant response time | 48h | 12h | -75% |
Estimated ROI: €320k/year in time saved (45 people × 1h30/day × 220 days).
Testimonial
"Our asset managers have regained time for analysis and client relations. Document search had become a bottleneck, it's now a competitive advantage."
— Director of Operations
Tech stack
- Python, FastAPI
- PostgreSQL, Qdrant
- Mistral 7B (on-premise)
- Azure AD SSO
- Docker, Kubernetes
Project completed in 12 weeks. Contact us for an on-premise deployment.
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