The National Property Parcel Dataset consolidates assessor, deed, mortgage, valuation, and sales history for U.S. parcels into a single spatially indexed record, ready for screening the moment you need it. For the first time, your acquisitions team can scan entire regional markets for off-market targets in the time it used to take to pull one county's records.

Most data vendors sell you a national license to millions of records you will never contact. BigGeo works differently.You tell us where you sell, and we cut you exactly that geographic slice of the dataset. A single city.
A cluster of ZIP codes. A metro area. A county. Whatever matches your territory. The result is a lean, CRM-ready file containing only the companies in the markets you actually work, delivered at a fraction of the cost of a full national license.

Acquisitions teams are not slow because they lack talent. They are slow because the data infrastructure underneath them was never built for speed. Assessor portals, county recorder sites, third-party AVM pulls, and manual deed searches were designed for one-off lookups, not portfolio-scale screening. Every deal that takes three weeks to underwrite is a deal someone else closes first.
Standardized parcel identifiers paired with precise coordinates and jurisdictional boundaries let you instantly map any target asset, confirm its legal footprint, and run proximity or clustering analysis against other holdings without a separate GIS step.

Know who owns a property today, where their mail goes, and how long they have held the asset. Long-hold, out-of-area owners are among the most reliable signals for off-market deal receptivity, and this data surfaces them at scale.

Complete transaction history plus multiple mortgage lien positions give you the capital stack context to assess distress, over-leverage, or motivated-seller conditions before you ever pick up the phone.

Three valuation perspectives on every parcel let you spot the gap between assessed value and market reality, validate your own underwriting assumptions, and prioritize targets where value dislocation creates opportunity.

BigGeo AI is live in ChatGPT today and shipping in Claude, giving your acquisitions and analytics teams direct access to this dataset through natural language, with no GIS software, no data pull request, and no waiting on a specialist. Ask which submarkets have the highest concentration of long-held industrial parcels with assessed values below AVM estimates, and get a governed, spatially grounded answer in seconds, not a data ticket. The underlying parcel data never leaves the governed compute path regardless of how you access it.
County portals return one jurisdiction at a time in inconsistent formats, and standalone AVM providers do not include ownership history, lien positions, or building characteristics in the same record. This dataset consolidates all of those attributes into a single standardized flat file across U.S. jurisdictions, and because it lives on BigGeo's spatially indexed platform, you can query across markets in the same workflow rather than reconciling files from a dozen sources.
Most in-house pipelines are maintained by one or two people, drift from source updates, and still require a GIS layer to do anything spatial with the output. This dataset arrives standardized, spatially indexed, and joinable to other datasets in BigGeo's DataLab, including consumer profiles via a documented key. The build-versus-buy math changes significantly when you factor in the ongoing maintenance cost and the deals you miss while the pipeline is catching up.
The dataset is sourced by Geopoint Data from assessor, deed recorder, and mortgage sources across U.S. jurisdictions. Refresh cadence varies by jurisdiction, which is the reality of any nationally consolidated property dataset. What BigGeo adds is that when the data updates, it updates inside the compute path, so every query you run is against the most current version available without you having to re-ingest or reprocess anything.
Once activated in BigGeo's DataLab, the dataset is available for direct query through the platform's compute engine, exportable for use in your existing tools, and accessible through BigGeo AI via ChatGPT or Claude for natural language queries. If your team uses spatial joins or proximity analysis, BigGeo's Velocity engine executes those operations at sub-second speed against the full parcel index without requiring you to pre-filter or downsample the dataset first.
BigGeo is not a data vendor relationship that requires an IT project. You request a sample, review the parcel records for your target markets, and activate through the Marketplace once you confirm the coverage meets your needs. Most acquisition teams are running their first market screen within days, not quarters. Book a 30-minute call and we will show you exactly what the dataset covers in the markets you care about most.