See which digital-health options AI treats as legitimate.
Logres evaluates how assistants describe your services, clinical model, availability, eligibility, geographic coverage, and trust signals when patients compare options.
A market view built for the evidence behind the answer.
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Audit legitimacy signals
See how the platform is framed when people compare available care options.
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Check coverage accuracy
Measure whether services, eligibility, geography, and care-model facts are described accurately.
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Trace trust evidence
Understand the public sources and proof behind the recommendation context.
01 Measure the questions
Start with the decisions that put your market on a shortlist.
A market baseline is designed around real buyer questions, not generic keyword volume. The work keeps the relevant services, entities, locations, and decision context visible from the first response to the evidence behind it.
Conditions and services
Measure the patient questions that connect care needs to the platform's stated services.
Geographic availability
Test how eligibility and state coverage are represented in AI-assisted decisions.
Clinical model
Review the public evidence explaining clinical teams, policies, and the care model.
02 Diagnose the evidence
Connect the answer to the public information shaping it.
Logres traces the sources, descriptions, and entity relationships that support an AI-generated recommendation. The result is a grounded view of what is present, missing, or inconsistent—not a generic content prescription.
Eligibility accuracy
Locate unclear or outdated policy, availability, and eligibility descriptions.
Medical and corporate evidence
Trace the institutional and owned sources that support trust claims.
Pricing and policy clarity
Identify public decision-support gaps without inferring unavailable facts.
03 Improve what is verifiable
Turn the evidence into a clear, reviewable path forward.
Recommendations stay tied to confirmed facts, target pages, and the source evidence behind them. Teams can review changes individually and keep implementation work separate from later AI re-measurement.
Care-model explanation
Make verified clinical, service, and eligibility information easier to locate and interpret.
Coverage structure
Prioritize grounded coverage and policy improvements by geography and service.
Authority support
Strengthen the evidence that helps assistants distinguish legitimate options.
Scope stays grounded in your market.
The baseline is a point-in-time measurement of AI-assisted consideration. It is not a promise of future recommendations or business outcomes.
Can Logres measure a national telehealth category?
Yes. The baseline can use national buyer questions alongside approved state or coverage context where that context is material.
Does it verify eligibility or clinical claims?
Logres records and flags public descriptions for review. Clients remain responsible for confirming clinical, regulatory, and eligibility facts.
Start with the answer buyers see before they meet you.
Logres scopes the questions, locations, entities, and evidence appropriate to telehealth & digital health.