HEALTHCARE · H2
AI Patient Triage Chatbot
Patients wait for hours and staff burn out. Your ED needs a GenAI triage agent that recommends the right care setting instantly and hands off to a clinician when acuity demands it.
CONVERSATIONAL TRIAGE • EMR INTEGRATION • HUMAN HANDOFF • MULTICHANNEL • HIPAA-ALIGNED
OnStak Healthcare AI Healthcare · Patient Triage 8 min read
THE PROBLEM
EDs are overwhelmed with patients who shouldn't be there.
Patients have no intelligent way to find the right care setting — so they default to the ED.
Up to 30% of ED visits are avoidable
Non-urgent cases consume ED capacity and extend wait times for genuinely acute patients. Patients self-route to the ED because there is no better option at the point of need.
Phone triage queues drive patients to give up
When patients face a long queue, most abandon the call and drive to the ED. Every dropped call is a patient that bypasses the right care setting entirely.
Frontline staff burn out on repetitive triage calls
Clinical staff spend large portions of their shift answering routine triage questions that follow predictable decision trees — a direct contributor to attrition in departments already running thin.
THE SOLUTION
A GenAI triage agent that routes patients to the right care — before they reach the ED.
Conversational, HIPAA-aligned, EMR-integrated. Live handoff when acuity demands it.
AI PATIENT TRIAGE CHATBOT · H2
OnStak deploys a Llama-class GenAI triage agent on the Cisco AI Pod — EMR-grounded, HIPAA-aligned, across web, voice, and chat in a single rollout.
How symptoms are captured
Conversational LLM captures symptoms naturally across web, voice, and chat — no forms.
Where patients are routed
ED, urgent care, primary care, or self-care — every recommendation grounded in EMR history.
When a human steps in
High-acuity cases trigger an immediate live handoff. The agent never replaces a clinician.
HOW THE SYSTEM WORKS
From symptom input to care pathway — in one conversation.
Entirely on the Cisco AI Pod within your network. No patient data leaves.
Patient describes symptoms in natural language
The GenAI agent engages conversationally across web, voice, or chat — extracting symptoms from free text, asking clarifying questions, maintaining clinical context turn by turn.
Agent grounds reasoning in the patient's EMR history
The agent pulls prior diagnoses, medications, and recent encounters from the EMR before making a recommendation — grounding the output in patient history, not generic symptom logic.
Agent recommends the right care setting — or escalates
Routes to ED, urgent care, primary care, or self-care based on severity and EMR history. High-acuity cases trigger an immediate live handoff — no delays, no ambiguity.
Every session is logged and feeds the learning loop
Each session is outcome-tagged and fed back into a continuous learning loop. Accuracy improves for your specific patient population without additional clinical resource.
PROOF OF CONCEPT
Measured across a multi-hospital health system rollout.
Multi-hospital rollout. Measured versus pre-deployment baseline.
25%
FEWER NON-URGENT ED VISITS
One in four non-urgent presentations redirected away from the ED.
35%
FASTER TRIAGE
From first contact to care setting decision.
90%
PATIENT SATISFACTION
Higher than phone-based triage across the same patient population.
HOW WE DO IT
From your first conversation to managed production — in four defined stages.
Joint delivery with Cisco. You define the criteria. We prove it before Scale.
Discover
We map your ED pressure points and triage volume to size the AI Pod and scope the deployment.
Pilot
EMR integration built. Triage agent tuned to your protocols and patient population.
Scale
Production rollout across all channels. Continuous learning loop activated.
Run
OnStak MINT operates the platform end-to-end. Model retrains on outcome data continuously.
OUR TECHNICAL STACK
Enterprise GenAI infrastructure — not a consumer chatbot bolted onto your EHR.
Llama-class inference on Cisco AI Pod. EMR-grounded. Fully managed by OnStak MINT.
CISCO INFRASTRUCTURE
GenAI inference stays within your network perimeter.
Cisco AI Pod — Medium / Large
Intersight
AI Defense
Splunk Observability
ONSTAK AI PLATFORM
Llama-class LLM with clinical protocol grounding and multi-channel deployment.
GenAI Triage Agent
Enterprise RAG
Voice AI
Rule Engine
Multichannel Deployment
COMPUTE AND RUNTIME
GPU-accelerated for low-latency conversational response.
NVIDIA AI Enterprise
NVIDIA Triton / NIM
vLLM
Red Hat OpenShift
INTEGRATIONS
Connects into existing clinical workflows with no disruption.
EMR / EHR via HL7
Nurse-Call Systems
Web and Chat
Voice / Telephony
AI Pod — Medium / Large
Handles concurrent multi-channel triage sessions at health system volume. Integrates with EMR and telephony via OnStak MINT — no disruption to existing infrastructure.