Rebuilding Trust Signals: How a HealthTech Platform Earned a Place in Clinical AI Answers

PulseCare operates in a category where AI models are correctly cautious: LLMs systematically under-cite health and clinical software vendors unless they meet strong E-E-A-T signals. Despite real clinical validation, PulseCare was being skipped over in AI-generated answers in favor of vendors with stronger public authority signals.

Their clinical outcomes data lived in gated reports. Their leadership team had no visible expertise footprint. Their review site presence was thin and inconsistent across G2, Capterra, and KLAS.

We treated this as a trust engineering problem, not an SEO problem:

• Published summaries and plain-language explainers of their peer-reviewed clinical validation, with proper Citation schema.
• Built out executive thought-leadership footprints on LinkedIn, industry podcasts, and named bylines in trade publications.
• Implemented Person and MedicalOrganization schema and connected it to their verified LinkedIn profiles.
• Ran a coordinated review-site refresh so the summary of PulseCare that AI models sampled from third parties actually reflected the product.

Within two quarters, PulseCare moved from being cited in 8% of clinical workflow prompts to 41%. More importantly, in the prompts that matter most — where buyers ask for "safe" or "validated" vendors — they are now named alongside the incumbents they previously lost to.