Practice Owners / Ops
Make AI measurable: time saved, acceptance rates, and safety triggers
A workflow-first platform that produces clinician-reviewed drafts and instrumentation you can turn into case studies (not vibes).
Pilot intro
We’ll share a pilot plan, integration posture, and the fastest path to measurable time-saved.
Artifact previewLive
Operations visibility
Make AI adoption measurable with acceptance, latency, and QA signals.
Step 01
Pilot
Single workflow
Step 02
Measure
Acceptance + edits
Step 03
QA
Safety checks
Step 04
Scale
Pack rollout
Ops dashboard
liveTime saved + acceptance
QA log
reviewEdits + safety events
Scorecard
readyBefore/after metrics
weekly ROI visibility
audited quality controls
Operational snapshot
01
Pick one workflow
Select a single lane to prove ROI and reliability.
02
Instrument acceptance
Track edits, adoption, and safety triggers.
03
QA cadence
Weekly review with clinician champions.
04
Scale with packs
Expand only after proven outcomes.
Ops dashboard
Time saved + acceptance by provider.
live
QA review log
Edits, variances, and safety events.
review
Pilot scorecard
Before/after metrics to decide scale.
ready
Operating model
Start with one workflow and measure it.
Clinician validation gate with acceptance + edits tracked.
Instrumentation: latency, cost per encounter, safety trigger rate.
Templates + rollout with weekly clinician champion review.
Expand packs only after the first workflow is proven.
Impact + modules
Impact
Weekly
ROI visibility
Draft acceptance + time saved tracked by provider.
Impact
Audited
Quality controls
Clinician edits + safety triggers captured.
Impact
Pack-based
Scale readiness
Expand modules only after proof.
Workflow packs
Urgent care, primary care, psych, and specialty packs.
Telemetry
Latency, cost per encounter, acceptance rates.
Compliance posture
Clinician review + guardrails baked in.
Change management
Templates, playbooks, and training flows.
Artifacts + rollout
Ops dashboard
Time saved, acceptance, and edit variance by team.
QA review log
Structured audit trails for each draft.
Pilot scorecard
Before/after metrics to decide expansion.
1
Week 1: Workflow selection
Pick the highest ROI lane and define success metrics.
2
Week 2: Pilot
Limited providers, daily feedback loops.
3
Week 3: Expand
Roll out to more clinicians; add second workflow.
4
Week 4: Operationalize
Staff training + continuous QA cadence.
Try it
Voice Intake Demo
WebRTC interview → structured packet
Clinician Cockpit
Review drafts + generate outputs
Radiology Workbench
Study image intake → structured findings
ER Admin Cockpit
Credentialing + coverage worklists
Psychiatry Demo
Consult + screening workflow
Personality & Screening
Entry point into screening
Pack snapshot
Workflow spine
Operational visibility for adoption, quality, and safety across workflow packs.
- 1Pick one workflowSelect a single lane to prove ROI and reliability.
- 2Instrument acceptanceTrack edits, adoption, and safety triggers.
- 3QA cadenceWeekly review with clinician champions.
- 4Scale with packsExpand only after proven outcomes.
Acceptance rateTime savedSafety trigger visibility
Artifacts
Ops dashboard
liveTime saved + acceptance by provider.
QA review log
reviewEdits, variances, and safety events.
Pilot scorecard
readyBefore/after metrics to decide scale.
Operating model
- 1) Start with one workflow: Pick one lane (urgent care intake, inbox autopilot, results manager) and measure it.
- 2) Clinician validation gate: Drafts are reviewed/edited before use; track acceptance + edits.
- 3) Instrumentation: Latency, cost per encounter, safety trigger rate, and time-to-note.
- 4) Templates + rollout: Tailor to site preferences and iterate weekly with a clinician champion.
- 5) Expand packs: Add adjacent modules only after the first is proven.
What you can measure
Time saved
minutes/visitProxy by note generation time + edit time delta.
Acceptance rate
% acceptedHow often drafts are accepted vs rewritten.
Safety triggers
safetyRed-flag rate + review false positives.
Cost + latency
$/encounterEnd-to-end latency and model cost per encounter.
Impact
Weekly
ROI visibility
Draft acceptance + time saved tracked by provider.
Impact
Audited
Quality controls
Clinician edits + safety triggers captured.
Impact
Pack-based
Scale readiness
Expand modules only after proof.
Module stack
Workflow packs
Urgent care, primary care, psych, and specialty packs.
Telemetry
Latency, cost per encounter, acceptance rates.
Compliance posture
Clinician review + guardrails baked in.
Change management
Templates, playbooks, and training flows.
Artifacts for operators
Ops dashboard
Time saved, acceptance, and edit variance by team.
QA review log
Structured audit trails for each draft.
Pilot scorecard
Before/after metrics to decide expansion.
Implementation plan
- 1Week 1: Workflow selectionPick the highest ROI lane and define success metrics.
- 2Week 2: PilotLimited providers, daily feedback loops.
- 3Week 3: ExpandRoll out to more clinicians; add second workflow.
- 4Week 4: OperationalizeStaff training + continuous QA cadence.
Try it
Voice Intake Demo
WebRTC interview → structured packet
Clinician Cockpit
Review drafts + generate outputs
Radiology Workbench
Study image intake → structured findings
ER Admin Cockpit
Credentialing + coverage worklists
Psychiatry Demo
Consult + screening workflow
Personality & Screening
Entry point into screening
Operator pilot
We’ll ship one measurable workflow end-to-end, then expand only after proving ROI.
Practice ops use case • clinician review required