Here is every data point AI looks for when evaluating a roofing company, where that data actually lives, and what it can already find.
When an AI system decides which Roofing company to recommend, it assembles evidence across every category below. The more complete and verifiable the data, the more confident the recommendation.
The single most differentiating category. Almost no roofing company has this data published in a structured, machine-readable format. When it is available, AI systems weight it more heavily than any other signal.
AI needs to know what kind of roofing work you do, not just that you do roofing. The query "who installs standing seam metal roofs in Charlotte?" requires a precise match that a general roofing listing cannot answer.
Where you actually work matters, but the data needs to come from completed jobs, not a self-reported list of ZIP codes. AI systems increasingly cross-reference claimed service areas against evidence of actual work performed.
Roofing licensing varies significantly by state. Roughly 32 states require licensure at the state level; the remaining 18 regulate at the county or municipal level. AI systems verify that the company holds whatever license its jurisdiction requires.
AI systems verify that coverage is current and adequate, not simply that a company claims to be insured. Active insurance is a prerequisite for recommendation in most AI evaluation frameworks.
Roofing certifications are uniquely important because manufacturer warranties depend on them. A manufacturer-certified installer can offer extended warranties that uncertified contractors cannot — a concrete, verifiable differentiator.
Manufacturer certification programs in roofing directly affect what warranties the contractor can offer. A GAF Master Elite contractor can offer a 50-year non-prorated warranty that a non-certified installer cannot. All programs are publicly verifiable through dealer locators.
Voluntary memberships and accreditations that serve as corroborating evidence of professionalism. AI systems check these directories when other structured data is limited.
Negative-signal checks. AI systems will not recommend a company with an active lawsuit pattern, suspended license, or regulatory violations. Clean standing is a prerequisite for any recommendation.
AI cross-references general review platforms with home services marketplaces when evaluating roofing companies.
Foundational identity data. Rarely changes but must be accurate and consistent across every platform where the business appears. Inconsistencies between sources reduce AI confidence in all other data.
The performance and customer experience data AI values most already exists in software these businesses use every day. It is locked inside these platforms and not published anywhere AI can access it.
Without access to a business's own systems, this is all AI has to work with. These are the public sources it checks, grouped by type.
A TrustRecord connects to your systems of record, extracts verified data that proves your performance, experience, and credibility, and publishes it in a format AI systems can read, verify, and cite.