Case Study: How CondoScan is simplifying Condo Purchases with LlamaIndex and LlamaParse

Overview

Buying a condo should be exciting — not stressful. Yet in Canada, buyers often face unexpected financial risks, such as surprise special assessments exceeding $60,000.

CondoScan, a Calgary-based startup, is addressing this critical problem by providing fast, comprehensive evaluations of condo financial health and lifestyle fit.

In just six months, CondoScan has gone live with a production solution that significantly reduces the time needed to review condo documents — from weeks to minutes — powered by LlamaIndex and LlamaParse.

The Challenge

Condo purchases in Canada often involve a complex and risky manual review process:

• Buyers must review 10–40 documents per property, totaling hundreds of pages (meeting minutes, financials, budgets).
• Manual reviews by experts can take ~2 weeks and still miss crucial risks.
• Buyers risk facing massive financial liabilities after purchase if issues are overlooked.

CondoScan set out to create a better system — one that could reduce review time, improve accuracy, and surface financial risks proactively.

The Solution: LlamaIndex + LlamaParse

CondoScan built a next-generation condo evaluation tool by deeply integrating LlamaIndex and LlamaParse into its core workflows.

Document Processing

• LlamaParse is used to prepare condo documents — including meeting minutes, reserve fund studies, and budgets — for vector database ingestion.
• Hundreds of pages per condo are parsed, cleaned, and structured automatically.

Knowledge and Analysis

• LlamaIndex powers all LLM interactions — from ingestion to retrieval to reasoning.
• Architected using Agent workflows, the CondoScan agent predicts financial loss risks, evaluate HOA (Homeowners Association) governance, and benchmark properties against industry standards.
• The system cross-references internal condo documents and external regulations (e.g., Alberta’s Condo Act).

End-User Experience

• CondoScan generates detailed, shareable reports that assess both financial and lifestyle risks.
• An integrated chat feature, built with agent workflows, allows users to ask natural language questions about a condo’s health.

Why CondoScan Chose LlamaIndex

Initially, CondoScan experimented with another leading framework — but found it limited. They choose LlamaIndex because of:

• Superior Agent Workflows: LlamaIndex’s workflows allowed agents to "think," reason, and select tools dynamically — unlike static prompt chains in other frameworks.
• Better RAG and Query Engines support: LlamaIndex offered superior pipelines and retrieval quality.
• Streamlined ETL: Document ingestion and processing were faster and more robust with LlamaIndex.
• Accuracy: LlamaParse’s highly accurate parsing ensures that no details are missed.

Ewan May, founder of CondoScan, noted:

“LlamaIndex felt like it was six months to a year ahead of alternatives. Setting up agent workflows was straightforward, and it actually feels like the system thinks — not just runs through steps.”

By building on LlamaIndex’s open-source foundation, CondoScan is setting a new standard for condo purchase transparency — and helping buyers make smarter, safer investments.

• Learn more about LlamaCloud, the turn-key enterprise solution from LlamaIndex
• Read up on Workflows, the core building block of agentic solutions in LlamaIndex
• Get in touch with us to see where LlamaIndex can take your company!