Organizations · group practices & health systems
01/ORGANIZATIONS / CUSTOM DEPLOYMENTS
Most clinical apps force you into their workflow. VibeCheck.luxury is built differently: an organization joins by putting its clinicians in member seats — and the platform adapts to your EHR, your care coordination model, and your compliance requirements. We bring the between-session intelligence layer. You keep the clinical system you already run.
01Clinical Framework
VibeCheck.luxury's STOICK protocol and six-area daily check-in can be reconfigured to match your organization's existing clinical model — whether that's ACT, CBT, DBT, trauma-informed care, or a proprietary framework. We do not impose a new modality. We instrument the one you already use.
A CCBHC running Seeking Safety + WRAP can configure VibeCheck.luxury to monitor the domains that matter to those programs, not our defaults.
02Data Architecture
Your data is encrypted at rest and in transit inside the AWS BAA boundary. Integrate with your existing EHR via HL7 FHIR or API. Export in the format your compliance team already accepts. We do not hold your data hostage.
Population dashboards feed directly into your existing Tableau / Power BI / CareQuality reporting pipeline.
03Workflow Integration
Pre-session briefs can be delivered via your existing scheduling system (Calendly, Acuity, EHR-native), your preferred channel (email, SMS, in-EHR notification), and your preferred format (bullet summary, SOAP draft, structured JSON for automation). We meet you where you already work.
VibeCheck.luxury's clinical intelligence layer is powered by Gemma, Google's open-weight model family — not a black-box "AI" feature with undefined behavior. Inference runs on Amazon Bedrock, inside AWS infrastructure covered by an executed Business Associate Agreement. Open weights mean the model is inspectable, versioned, and doesn't change underneath your deployment. We handle the clinical prompting layer.
An open-weight model inside a BAA-covered boundary means no vendor can change, retire, or retrain the model underneath your deployment — and your clinical data never trains anyone's next release. The model version your compliance team reviews is the model version that runs.
The LLM does not "chat" with your clients. It processes structured check-in data through a clinically designed prompt chain — informed by Lambert ROM methodology, sudden-gains literature, and Matthew Sexton's 13 years of clinical practice. The output is a clinical brief, not a conversation.
The exact model version and generation settings behind every output are pinned and disclosed — no floating "latest" that shifts underneath you. Every clinical output is reviewed and signed by the licensed clinician before it enters the record. Prompt and response content is intentionally not retained, to minimize PHI in logs. Nothing is hidden behind an "AI" label.
AI capacity is allocated as AI interactions — a completed clinical action (a pre-session brief, a SOAP draft, a pattern summary, a longitudinal report), never a raw compute unit. Per-seat allocations, use-case mix, and multi-site pooling are set with your team at signature.
05/NEXT STEP
30 minutes with Matthew. We review your current stack, map the integration points, and scope the customization. No SDR. No sales deck. Just clinical infrastructure, tailored to your system.
The EMR is currently in beta. Enterprise access is a conversation. 5–500+ clinician seats; BAA, implementation planning, and clinical onboarding included. Data architecture and workflow integration scoped in the first call.
Diligence ahead of the call: data security — the boundary, the model, and what we deliberately do not claim · clinical safety — the four gates the AI cannot pass