Patient cases that intake, consent, and route themselves.
Phyllis builds and extends your entire healthcare service operation — any case type, consent policy or care-team routing — grounded in your live instance and staged for your approval.
Built by ServiceNow architects — CMA-grade by default
Grounded in your instance
Approval-gated delivery
CMA-grade documentation
Self-heal on your approval
A quick scroll through what Phyllis can do
Scan HCLS setup
Healthcare case type
Consent policy
Privacy notice
Care-team routing
Case lifecycle
Patient portal
Appointment intake
Directive on file
Priority tiers
Consent tracking
Case reporting
Scan HCLS setup
Healthcare case type
Consent policy
Privacy notice
Care-team routing
Case lifecycle
Patient portal
Appointment intake
Directive on file
Priority tiers
Consent tracking
Case reporting

Questions?
We’re glad you asked.
She sets up the healthcare service operation end to end: the case types, consent and privacy handling, care-team routing, intake, and the patient portal that fronts it all. The day-to-day patient cases and consents your team raises stay in your hands — Phyllis builds the engine that intakes, routes and records them, not the records themselves. You get a governed care-operations process ready to run.
Yes. Healthcare service delivery has its own shape, and Phyllis builds on the healthcare foundation rather than forcing a generic model onto it. She works with what your vertical already provides instead of reinventing it, so the result feels native to how healthcare teams actually operate.
Consent and privacy are treated as first-class configuration, authored correctly and kept auditable. Policies are never quietly discarded — when one is retired it's deactivated, so the full history patients and auditors rely on stays intact. You get a compliant, traceable consent process rather than a black box.
Correct. Phyllis reviews your instance, proposes a plan, and only builds once you explicitly approve. Every change is staged for review and is reversible, and she never completes or activates anything on your behalf. You stay in control of what reaches production.
Every claim is cited back to your own live instance — what's actually configured today, not out-of-box assumptions. On migrated or long-running instances the real setup drifts from the shipped baseline, so grounding in your evidence is what makes the plan trustworthy. You get findings you can verify, not assertions.































