Real Systems. Real Results.

A real estate PE firm specializing in flex industrial acquisitions needed to identify acquisition targets across the Southeast US. Their team was manually researching properties — cross-referencing county records, satellite imagery, and zoning data one parcel at a time.

We built a property classification pipeline that processes bulk GIS data through a weighted scoring algorithm. The system integrates with county GIS APIs, uses dual-database architecture, and delivers CRM-ready prospect lists.

We also built a custom CRM with automated call transcription, property matching, and follow-up scheduling — replacing enterprise tools that cost over $15,000 per year with a system running at $168 per month.

A commercial real estate firm investing in Industrial Outdoor Storage properties needed a systematic way to identify acquisition targets. Manual research meant 30 minutes per property across thousands of potential parcels.

The key insight: IOS inverts traditional CRE logic. Instead of high building coverage, you want low building coverage — the value is in the land, not the buildings. Generic CRE analysis tools get this backwards.

We built a pipeline that acquires bulk GIS data, integrates Microsoft Building Footprints via spatial joins, calculates coverage ratios for every parcel, and scores properties across 6 weighted dimensions. Deliverables included interactive maps with satellite imagery, scored workbooks, and CRM-ready exports.