AI-assisted Medicare qualification with structured human hand-off
Reported operational saving: approximately $1.2M per year.
An AI-assisted Medicare and ZIP-code qualification workflow with real-time decisioning, structured hand-off and operational reporting, credited with a reported saving of about $1.2M per year.
US Medicare advisory operations. Callers are qualified on eligibility and geography before reaching licensed humans, so agent time is spent only on qualified conversations.
Rôle : Qualification workflow and production engineering
Founder contribution delivered as part of professional work at BlandLabs.
- Reported operational saving per year
- $1.2MReported operational saving per yearFounder contribution at BlandLabs
- Eligibility decisioning before callers reach licensed humans
- Real timeEligibility decisioning before callers reach licensed humansFounder track record
- Operational reporting and production monitoring
- Every callOperational reporting and production monitoringFounder track record
Le système
Ce qui a réellement été construit
- Medicare and ZIP-code eligibility qualification
- Agent decision path with escalation to humans
- Lead scoring and structured hand-off
- Operational reporting on every call
- Production monitoring
Expérience produit
Issu du système livré
Technologie
Stack vérifiée
Seules les technologies confirmées dans le code source, la documentation du projet ou le déploiement en production sont listées.
- Voice AI qualification workflow
- Real-time intent detection
- Lead scoring and analytics pipeline
Livraison
Périmètre de responsabilité
- Qualification and decision path design
- Reporting and monitoring
Preuves
Sources
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