PermitPortal

PermitPortal — A continuously refreshed entitlement-risk layer over US local government land-use decision-making. Agents read governing-body vote records, planning-department filings, assessor data, and public-comment/opposition activity across 3,200+ jurisdictions on a 2-hour cadence, and derive two scored products: (1) a Jurisdiction Risk Score covering every US authority having jurisdiction across 11 dimensions — voting history, approval velocity, staff receptivity, legislative environment, design burden, incentive landscape and community opposition among the named dimensions, with the sco…

PermitPortal offers (Alternative, Reference, Geospatial, Sentiment, Esg) — Printed: 3,200+ US jurisdictions (AHJs) each scored across 11 dimensions — roughly 35,000 live score cells, refreshed on change rather than on schedule — plus national parcel coverage screened on geometry, zoning, use tables, ownership, infrastructure proximity and flood zone, which implies the full national parcel layer (tens of millions of parcels) rather than a curated subset. Under that sits continuous ingestion of every published agenda, vote record and public comment entered into the record for tracked jurisdictions on a 2-hour cycle. So volume is three-layered: a modest scored-jurisdiction table, a very large parcel table, and an unbounded growing archive of parsed meeting and vote records..

Explicitly aimed at pre-spend site selection for large-scale development across asset classes — manufacturing and industrial, data centres (noise performance standards named), logistics (truck-traffic thresholds named), and multifamily (density opposition named). Beyond that: entitlement-risk underwriting and pricing for developers before an LOI or capital commitment; jurisdiction arbitrage in site shortlisting (comparing approval velocity and vote history across candidate counties); community-opposition early warning for projects likely to attract organised resistance; municipal and legislative risk monitoring for portfolio holders; land-valuation and land-banking models in which entitlement probability is a direct input to land basis; insurance and surety underwriting of development risk; and — most transferably — labelled training data for predicting regulatory and civic approval outcomes, since the corpus pairs named decision-makers' actual recorded votes with application types at national scale.