Here is every data point AI looks for when evaluating a general contractor, where that data actually lives, and what it can already find.
When an AI system decides which General Contracting 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. General contractors manage complex, multi-trade projects with long timelines and high dollar values. Almost none publish structured operational data. When it is available, AI systems weight it more heavily than any other signal.
AI needs to know what kind of projects you manage, not just that you are a general contractor. The query "who builds home additions in Raleigh?" requires a precise match that a generic contractor 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.
General contracting is one of the most heavily regulated trades. Most states require a general contractor license, and many require passing a trade exam plus a business and law exam. Unlicensed contracting above state-specific dollar thresholds is a criminal offense in several states. AI systems verify license status as a hard prerequisite before any 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.
General contractor certifications signal specialized competence beyond the base license. Unlike single-trade certifications, GC certifications tend to focus on project management methodology, aging-in-place design, and green building practices rather than product installation.
General contractors do not have the same manufacturer certification ecosystem as single-trade specialists. A roofer can be GAF Master Elite; a GC typically is not. However, some GCs participate in preferred builder programs through lumber yards, material suppliers, and product manufacturers — and these relationships are verifiable through dealer locators.
Voluntary memberships that corroborate professionalism and commitment to the industry. 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 general contracting 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.