Active real-estate intelligence platform and AI-powered deal automation
The modern U.S. real-estate industry suffers from a deep structural failure: most market participants rely almost entirely on late, publicly visible information. The moment a deal or asset appears on public listing boards, competition turns savage, bidding wars inflate prices, and developer margins are erased. An entire market makes decisions from the same visible data at the same time, so the only skill that truly wins is how fast someone can reach the source before everyone else. Every extra week of delay forces the contractor, developer, or company to pay a higher premium for the same asset, until the opportunity becomes an ordinary trade or disappears completely.
PermitHeat was built to shatter this blindness through a shift to active data ingestion called Active Data Ingestion. The system uses a proprietary AI engine that intercepts and processes complex, dispersed, unstructured real-time data streams from layers of municipal bureaucracy and multiple official U.S. government sources. By refining these signals, the platform creates absolute information asymmetry. It identifies assets inside and outside the market that are at their precise economic or planning inflection point, and lets users reach decision-makers directly with zero competition, months before the rest of the market even realizes a deal exists.
Built for framing contractors, construction firms, plumbers, electricians, suppliers, and field-service providers across the United States. This channel replaces expensive, blind advertising budgets. The system detects mega-scale projects the moment they are officially approved by the municipality and connects the user directly to the verified contact details of the property owner through a Data Fusion process that does not depend on gatekeepers.
Built for acquisition companies, developers, institutional investment funds, and wholesale deal finders. The system identifies on-market and off-market assets and parcels, automatically calculates declared burden and structural risk costs, and instantly produces an optimal target offer called Target Offer that reflects a meaningful double-digit discount below market price to secure margin on the day of acquisition.
Gives every signal in the system a machine-learning-based score from 1 to 100, composed of four hard maturity metrics.
Uses large language models to automatically analyze the essence of the engineering situation and draft, with a single click, personalized messages and emails that turn a cold outreach into a warm, fact-backed business conversation in seconds.