Generate Real-Time CRE Comp Reports with a Custom AI System

Mid-market commercial real estate brokerages are often caught between high-value, bespoke client analysis and the repetitive, manual tasks required to produce it. Brokers and analysts commonly spend 2-4 hours per property just compiling a comparative market analysis (CMA) report. This starts with pulling property data from various external subscriptions like CoStar, Buildout, and Reonomy, then cross-referencing against the firm's proprietary deal history, which might reside in an internal Supabase database or spreadsheets.

The workflow is inherently fragmented. An analyst needs to navigate separate platforms, exporting data to Excel, then manually normalizing fields—like property size, lease rate, or cap rate—that are labeled differently across sources. This is followed by the painstaking process of selecting the most relevant comps, calculating averages, and finally copying and pasting information, images, and maps into a client-ready, branded template, often using desktop publishing tools like InDesign or PowerPoint. This manual aggregation not only consumes valuable time but also introduces a significant risk of transcription errors and inconsistencies, which can erode client confidence.

The fundamental challenge is that data providers like CoStar deliver data, not tailored workflows. Their platforms are designed as closed ecosystems, and while some offer APIs, these are primarily built for basic data ingestion, not for deep, bidirectional integration with a firm's unique analytical processes. Off-the-shelf tools cannot account for a brokerage’s specific internal knowledge, historical deal context, or custom reporting standards. This forces brokers to bridge the gap manually, preventing efficient generation of not only CMAs, but also automated LOI and proposal drafts, intelligent tenant and buyer prospecting, or streamlined investor reporting. The result is valuable broker time diverted from deal-making to data wrangling, impacting profitability for commission-based firms.

Syntora's approach begins with a comprehensive data audit and discovery phase. We would map every location where your firm stores relevant comp data, from structured internal databases (e.g., Supabase) and CRM systems (e.g., Salesforce, HubSpot) to third-party subscriptions like CoStar, Buildout, and Reonomy, and even unstructured sources such as PDF lease agreements or offering memorandums. This initial phase defines the data flow and integration points, culminating in a detailed architectural plan and clear scope before any development begins.

The core system would be engineered as a modular, event-driven architecture, typically using a FastAPI service deployed on AWS Lambda for scalable, cost-effective, and on-demand processing. When a broker initiates a report request, this service would orchestrate parallel API calls using Python's httpx to retrieve external data from CoStar, Buildout, and Reonomy. Concurrently, it would query your internal databases for proprietary deal history. For unstructured documents, the Claude API would be employed to extract critical data points—such as rent, escalations, options, and expiration dates from lease documents—a pattern Syntora has successfully implemented for complex financial document processing in other domains. This parallel processing rapidly consolidates disparate sources into a normalized dataset.

The delivered system would expose a user-friendly web interface where brokers can input property addresses, select specific criteria, and trigger report generation. The system would then populate your firm's branded templates with the extracted and normalized data, quickly generating client-ready PDF reports. As part of the engagement, clients receive the full Python source code in their GitHub repository, alongside a comprehensive runbook for maintenance and operational guidance. The system is designed to run within your firm's own AWS account, offering full ownership and control, with typical hosting costs under $50 per month. Clients would need to provide API keys for their existing subscriptions and access to internal data sources and template designs.