Founder
Danielle Holmes
MSN, RN, CCRN, NI-BC · NSF SHINE Fellow · Founder, Clinically AI
Built by a CCRN who understands what happens when technology enters the bedside, the chart, and the room.
Danii Holmes is a dual-certified nurse with nearly a decade of critical care, trauma, nursing leadership, and informatics experience at Level 1 academic medical centers. Her work lives at the intersection of bedside nursing, clinical education, documentation, patient privacy, and healthcare AI.
She founded Clinically AI around a problem she watched up close: clinical AI tools, recording-capable devices, and digital documentation workflows are entering care faster than nursing education, privacy language, and practical policy can keep up.
Why Clinically AI Exists
Clinical AI literacy and privacy protection for the bedside.
Clinically AI was created for the messy middle where healthcare technology actually lands: busy units, small practices, patient rooms, charting workflows, education gaps, privacy concerns, and clinicians trying to do the right thing without clear language or tools.
AI is moving faster than education.
Nurses are being asked to work around AI-enabled documentation, alerts, analytics, prediction tools, and automation before many teams have been taught how those systems work or where bias can enter.
Recording-capable devices are entering clinical spaces.
Smart glasses, phones, ambient tools, and AI scribes create new privacy questions. The issue is not only staff comfort. It is also the privacy of other patients, visitors, and clinical conversations nearby.
Healthcare needs practical language.
Clinicians and practice owners need tools that communicate clearly without overpromising. Clinically AI builds notice-first materials, education, and consulting support that are designed to be understandable and claim-safe.
Why a Nurse Is Building This
Because bedside reality changes how technology should be designed.
Clinically AI starts from the nursing workflow: the interrupted shift, the unstable patient, the chart that needs to be accurate, the family member recording in the room, the alert that may or may not fit the patient in front of you, and the clinician who still has to make a safe judgment.
That is why the company does not treat AI literacy, documentation, privacy, and equity as separate issues. In real clinical spaces, they overlap.
Founder Lens
Technology should support clinical judgment, not replace it. It should make privacy easier to explain, not harder to defend. It should help nurses understand the systems shaping their work.
Clinically AI is built from that position: practical, nurse-informed, privacy-aware, and clear about what technology can and cannot safely claim.
What Clinically AI Builds
A three-part company for clinical AI literacy, privacy-zone workflows, and open standards.
Education & Consulting
Clinical AI literacy for nurses and healthcare teams.
Courses, speaking, consulting, and practical standards that help nurses understand AI tools, clinical decision support, documentation risk, bias, and acceptable AI use.
Privacy Zone Program
Notice-first privacy tools for recording-aware clinical spaces.
Digital badge kits, response toolkits, hosted notice pages, QR workflows, and development concepts that help practices communicate privacy expectations without claiming to block or detect recording.
Open Standard
A credibility layer for signs, QR pages, and device-aware notices.
The Privacy Zone Beacon Specification is a coming-soon open standard intended to support clearer, machine-readable privacy notices for healthcare and other sensitive spaces.
Research Direction
From bedside pattern recognition to algorithmic bias research.
In fall 2026, Danii begins a PhD in nursing at UMass Amherst as an NSF SHINE Fellow, advised by Dr. Joohyun Chung. Her research direction focuses on NLP-driven EHR analysis, algorithmic bias, clinical decision support, and equity in health data systems.
Clinically AI connects that research direction to the practical education, tools, and privacy language clinicians need now.
Founder snapshot
- Critical care and trauma nurse
- Double Masters degree in nursing and information technology
- Certified in critical care and nursing informatics
- Nursing Professional Development Practice Leader
- Incoming NSF SHINE Fellow at UMass Amherst
- Founder of Clinically AI LLC
- 2024-2026 VP, Sigma Theta Tau, Beta Psi Chapter
- 2023-2025 Technology Co-Chair, Delta Sigma Theta Sorority, Incorporated, Portland Alumnae Chapter
- BLS, PALS, Stop The Bleed instructor
Clinically AI Standard
Clear enough for bedside use. Careful enough for healthcare.
Clinically AI provides education, consulting, digital products, and privacy-zone support. Clinically AI does not provide medical advice, legal advice, compliance certification, guaranteed search placement, or recording-blocking technology. Clinical tools and education materials support learning, workflow, communication, and privacy awareness; they do not replace licensed clinical judgment, escalation, emergency response, or employer policy.