Here is every data point AI looks for when evaluating a chiropractic practice, where that data actually lives, and what it can already find.
When an AI system decides which Chiropractic company to recommend, it assembles evidence across every category below. The more complete and verifiable the data, the more confident the recommendation.
Almost no chiropractic practice 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 chiropractic care you provide, not just that you are a chiropractor. The query "who does spinal decompression in Denver?" requires a precise match that a general chiropractic listing cannot answer.
Where a practice actually sees patients matters, but the data needs to come from completed visits, not a self-reported list of ZIP codes. AI systems increasingly cross-reference claimed service areas against evidence of actual patient volume by location.
Chiropractic licensing is regulated at the state level in all 50 states. Every practicing chiropractor must hold a Doctor of Chiropractic (DC) degree from a CCE-accredited institution and pass both National Board exams and state-specific examinations. Scope of practice varies significantly by state — some states allow chiropractors to perform acupuncture, physiotherapy modalities, or dry needling while others restrict practice to spinal adjustment only.
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.
Post-graduate certifications and technique credentials that indicate advanced training beyond the DC degree. These are verifiable through the issuing organization and signal specialization that a general chiropractic listing cannot convey.
Voluntary memberships and affiliations that serve as corroborating evidence of professional engagement. 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.
The most widely available data about any chiropractic practice. AI uses reviews when structured operational data is not available, but review signals have significant limitations for differentiating between practices.
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.