Here is every data point AI looks for when evaluating a solar installation company, where that data actually lives, and what it can already find.
When an AI system decides which Solar Installation 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 solar installer 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 solar work you do, not just that you install solar. The query "who installs commercial solar with battery backup in Austin?" requires a precise match that a generic solar installer 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.
Solar installation is heavily licensed because it is fundamentally electrical work. Every state requires electrical contractor licensing, and several states have solar-specific license classifications. AI systems verify current license status before making a recommendation.
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.
NABCEP (North American Board of Certified Energy Practitioners) is the gold standard in solar — the equivalent of NATE certification for HVAC. A NABCEP-certified installer signals a level of competency that no amount of Google reviews can convey.
Solar equipment manufacturers run authorized installer programs that vet contractors for training, installation quality, and sales volume. These designations are a strong quality signal — manufacturers stake their brand reputation on certified installers.
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 solar installation 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.