Automate Your CRE Comp Reports: From 4 Hours to 10 Minutes

Brokerages rely on data from CoStar, Buildout, and Reonomy, but getting that data into a client-ready report is entirely manual. The problem is not the data quality, but the extreme effort required to synthesize it. Brokers log into each platform, run searches, and then copy-paste dozens of data points like price, square footage, and cap rate into an Excel sheet or Word document, one property at a time.

Consider a mid-market broker in Chicago comping a 50,000 sq ft industrial property. The broker pulls 15 potential comps from CoStar, 10 from Reonomy, and checks their internal deal history in Buildout, finding 5 overlaps. They must then manually deduplicate the list, normalize field names ('Sale Price' vs 'Price'), and re-format dates and currency. This copy-paste work consumes 2-3 hours before any real analysis can begin, and a single typo in a key metric can undermine the entire report.

The structural issue is that these platforms are designed as data silos, not as interoperable systems. Their APIs, when available, are built for pulling discrete data points, not for generating holistic reports that combine competitor data. The business model of these data providers incentivizes keeping users logged into their platform. This creates a permanent bottleneck where your most experienced brokers spend hours on low-value, repetitive tasks that are critical but non-billable.

The result is a slow, error-prone process that limits how quickly you can respond to client requests. As your deal volume grows, the time lost to manual report building scales directly with it. This operational drag keeps senior talent tied up in administrative work instead of closing deals.

The engagement would start with a technical audit of your brokerage's current comp reporting process. Syntora would map every data source you use, document the specific fields you pull for each property type, and review your existing report templates. This discovery phase ensures the system is built around your specific workflow. You would receive a technical specification that outlines the complete data flow for your approval before any code is written.

The technical approach uses a Python-based data pipeline hosted on AWS Lambda for efficient, event-driven processing. The system would connect to official APIs where available and use secure browser automation for platforms without them. The Claude API would handle complex data extraction from unstructured property descriptions and normalize field names across sources. All normalized data is structured in a Supabase database, creating a clean, historical comp library for your firm.

The delivered system is a simple web interface where a broker inputs a subject property address. The pipeline runs, pulls and normalizes comps, and generates a client-ready report in your branded Word or PDF template within 10 minutes. You own the source code, the system runs in your cloud account, and it fits into your workflow without requiring your team to learn a new platform.