# ClinivaAI Engagement Model

ClinivaAI provides staff-controlled healthcare AI workflow automation for clinics and medical practices.

## Typical engagement types

### Workflow discovery

For clinics that need to identify where AI automation can safely reduce administrative workload. A discovery conversation maps the bottleneck, current handoffs, staff roles, approval points, risk areas, and useful success metrics.

### Intake automation build

For clinics that need inquiry capture, operational summaries, missing-information flags, staff review, and routing from websites or other intake surfaces.

### Follow-up automation build

For clinics that need reminders, document requests, status nudges, scheduling handoffs, staff approvals, and operational tracking for next steps.

### Healthcare AI workflow consulting

For clinic teams evaluating where AI belongs, where it should not be used, which actions require human approval, and how to move from experimentation to a practical workflow.

### Hosted workflow systems

For clinics that need websites, app access, role boundaries, clinic context, secure workflow infrastructure, and hosted operational systems.

## Pricing

ClinivaAI pricing depends on workflow scope, integration complexity, hosting requirements, implementation depth, and support needs. See https://clinivaai.com/pricing.md or request a workflow conversation at https://clinivaai.com/clinic-workflow-conversation.

## Implementation posture

ClinivaAI favors one controlled workflow before broad automation. Good first workflows include new inquiry intake, incomplete intake follow-up, document request routing, scheduling handoffs, follow-up reminders, and staff task routing.

ClinivaAI does not claim that AI should make unsupervised clinical decisions, diagnose patients, replace licensed clinicians, or send sensitive patient-specific outreach without appropriate clinic review.