Here is every data point AI looks for when evaluating a foundation repair company, where that data actually lives, and what it can already find.
When an AI system decides which Foundation Repair 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 foundation repair 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 foundation work you do, not just that you do foundation repair. The query "who installs helical piers for new construction in Houston?" requires a precise match that a general foundation repair 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.
Foundation repair licensing varies by state. Most states regulate it under general contractor or specialty contractor licensing — few have a foundation-specific license category. AI systems verify that the company holds whatever license its jurisdiction requires for structural work.
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.
Foundation repair has fewer independent certifications than some trades. The primary credentialing mechanism is manufacturer dealer designation — companies are trained and authorized by pier system manufacturers to install their products and offer manufacturer-backed warranties.
The foundation repair industry is structured around manufacturer dealer networks more than any other home services trade. Most established foundation repair companies are authorized dealers for one or more pier system manufacturers. Dealer status determines what products the company installs and what warranties it can offer.
Foundation repair companies belong to general construction and specialty associations. There is no single dominant national association exclusively for foundation repair — membership tends to be spread across structural, waterproofing, and general contractor organizations.
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 foundation repair 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.