A law-firm AI citation audit measures one practice area and market at a time, because “family lawyer in Fresno” and “car-accident lawyer in Fresno” draw different competitors and sources. Each prompt runs several times through platform APIs. The report quotes the dated answers, counts mention and citation rates, and identifies the public sources that recur.
Legal searches are particularly sensitive to wording. A broad “best lawyer” prompt, a service-specific question, and a problem-specific question can return different shortlists. The useful report preserves that wording and never converts an AI mention into a quality rating. A competitor appears because the platform named it in that sampled run, not because the auditor endorsed it.
What the record changes
The entity pass checks the firm's name, locations, phone numbers, attorney names, and practice-area pages against the sources in the answers. The fix list stays on factual consistency and pages the firm controls. State bar advertising rules remain with the firm and its counsel, so the audit does not provide a compliance verdict or promise that a change will produce a future mention.
- The research found specialist AI-visibility agencies quoting one-off audits from roughly £1,500 to £5,000, with some delivery windows measured in weeks.
- The audit uses rates over sampled API runs and keeps the date and verbatim answer behind every published number.
- Legal paid-search costs make a public local-answer surface more useful for demand sampling than buying broad law-firm clicks.
How to use this answer
An AI citation check defines buyer-intent prompts for one service and place, runs each prompt several times through the platforms' APIs, and records every named practice and cited source. The report uses mention and citation rates over a stated run count because a single answer can change on the next run. Entity checks then compare the practice's name, address, phone, service, and location pages across the sources that appeared.
- Choose the service, city, and buyer question before naming the practice you want to measure.
- Run each prompt several times on each API, save the verbatim dated answers, and calculate rates from the full run set.
- Inspect the cited directories, articles, and local pages for entity consistency, then prioritize fixes on surfaces the practice controls.
Where the service stops
Reality Contact, LLC runs prompts through platform APIs and reports dated sampled answers. API output is a proxy for consumer-app output and can differ from it. We report who appears and which sources the answer cites. We do not get a practice named, cited, ranked, or recommended, and we do not rate competitors. This is not legal advice or financial advice, and it is not advertising-compliance advice.
Sources: Nbound AI visibility audit guide; Veza Digital AI search audit; OpenAI web-search documentation.