HealthcareIllustrative Client Case
Automating patient intake and initial triage using strict HIPAA-compliant conversational AI.
Client: National Healthcare Network (Anonymized)
LLM RoutingVector DBHIPAA API GatewayReact
The Challenge
The healthcare network's patient support center was overwhelmed with routine scheduling, intake, and non-emergency medical inquiries, leading to 45-minute average hold times and a severe drop in patient satisfaction.
System Architecture Diagram (Illustrative)
Raw Data Input
AI Processing Engine
LLM / Vector DB
Structured Output
Our Engineering Approach
We engineered a secure, HIPAA-compliant conversational AI agent integrated directly into their EHR (Electronic Health Record) system. The agent uses strict fallback mechanisms, immediately routing to human operators if uncertainty thresholds are crossed or if emergency intent is detected.
The Measurable Outcome
Resolved 68% of support requests automatically Reduced wait times from 45 min to under 2 min Saved $1.2M annually in triage operations overhead
Impact Metrics
Illustrative Data
45
2
Avg Hold Time (min)
0
68
Automated Resolution (%)
Before Qeltrava
After Implementation
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