Clinical staff spending significant time on patient FAQ calls, appointment rescheduling, and intake data collection that AI could handle consistently?
Generic chatbot platforms not meeting HIPAA requirements or unable to integrate with your EHR for appointment and patient data access?
Healthcare AI Chatbot Development
HIPAA-compliant AI chatbots for healthcare -- patient intake, symptom triage, FAQ automation, and appointment management that reduce administrative burden without compromising clinical accuracy.
Built with the HIPAA architecture, clinical workflow understanding, and EHR integration that healthcare AI requires -- not generic chatbot platforms adapted for healthcare use.
HIPAA-compliant architecture with BAAs with all AI infrastructure providers
EHR integration for patient identification, appointment data, and care plan access
Clinical accuracy guardrails -- scope-limited responses with clear escalation to clinical staff
Patient intake, symptom collection, and FAQ automation with consistent, auditable responses
RaftLabs builds custom healthcare AI chatbots -- HIPAA-compliant conversational AI for patient intake, symptom triage, appointment scheduling, clinical FAQ automation, and care management support. Healthcare AI chatbots integrate with EHR systems via FHIR for patient data access and appointment management. All PHI handling follows HIPAA requirements with encrypted storage, audit logs, and Business Associate Agreements with AI infrastructure providers. Most healthcare AI chatbot projects deliver in 8--14 weeks at a fixed cost.
HIPAACompliant architecture
·EHRIntegration via FHIR
·24/7Patient support coverage
·FixedCost delivery
Healthcare AI chatbots require clinical scope control, not just chatbot infrastructure
Generic chatbot platforms can answer patient questions -- but without scope controls and escalation design, they can also give clinically inappropriate responses that create liability and erode patient trust. Healthcare AI chatbots require specific design decisions that general-purpose chatbot platforms don't make by default.
We build healthcare chatbots with scope-limited response design: the chatbot handles what it's explicitly trained to handle (appointment queries, intake collection, care plan FAQ, medication reminders) and escalates to clinical staff for anything outside that scope. Clear escalation design is as important as the chatbot functionality itself.
What we build
Patient intake automation
Conversational patient intake before appointments -- collecting chief complaint, symptoms, duration, severity, and relevant history in a guided conversation before the patient arrives or joins a telehealth consultation. Intake data structured and sent to the EHR as a pre-visit note or directly into the provider's workflow. Pre-appointment form completion rates improve when intake is conversational rather than a static form. Reduces the intake time providers spend at the start of appointments on information that could have been collected in advance.
Symptom collection and triage support
Structured symptom collection following clinical protocols -- asking follow-up questions based on initial symptom reports to collect the information your clinical team needs for triage. Urgency flagging for symptom patterns that suggest time-sensitive conditions, with clear escalation to clinical staff for review. The chatbot does not diagnose -- it collects structured symptom data using your clinical team's triage logic and routes to the right care pathway. Clinical triage rules defined with your clinical team and reviewed by a clinician before deployment.
Appointment scheduling and management
Patient-facing appointment scheduling via chat -- checking availability, booking, rescheduling, and cancelling appointments with EHR or scheduling system integration. Automated appointment reminders with confirmation and rescheduling options. Pre-appointment preparation instructions (fasting requirements, medication holds, what to bring). Post-appointment follow-up with care instructions and next appointment reminders. Reduces appointment-related calls to your front desk without requiring patients to log into a patient portal.
Clinical FAQ and care plan support
Answering common patient questions about their care plan, medications, and post-procedure instructions -- sourced from your clinical documentation and reviewed by your clinical team for accuracy. Medication reminder and adherence support for patients on complex regimens. Post-discharge instructions and follow-up guidance for surgical patients. The chatbot answers within the scope of approved clinical content and escalates questions outside that scope to clinical staff. Response auditability for compliance and quality review.
HIPAA-compliant infrastructure
Business Associate Agreements with all AI infrastructure providers handling PHI -- LLM API providers, data storage, and communication platforms. Encrypted PHI handling in transit and at rest. Audit logging of all patient interactions with PHI access for compliance review. Patient identity verification before PHI access. Session management with appropriate timeout for inactive sessions. The compliance infrastructure that makes AI chatbots viable in a regulated healthcare environment.
EHR integration and data access
FHIR R4 integration with your EHR for patient identity verification, appointment data, care plan access, and medication lists. SMART on FHIR authentication for secure patient identity confirmation before PHI access. Appointment booking write-back to your EHR scheduling system where the EHR API supports it. Intake data submission as structured FHIR resources or clinical notes. The EHR integration that makes the chatbot aware of your patients' actual care context.
Frequently asked questions
Healthcare AI chatbots work well for: appointment scheduling and management (no clinical judgment required), administrative FAQ (hours, location, insurance accepted, referral process), structured symptom and intake collection following defined protocols, care plan FAQ sourced from approved clinical content, medication reminders, and post-visit check-ins using defined scripts. Clinical staff should always handle: clinical advice beyond what's in approved FAQ content, any symptom presentation the triage protocol flags as potentially urgent, questions about diagnosis or treatment decisions, and any patient expressing distress or safety concerns. The chatbot's escalation design defines these boundaries explicitly -- the chatbot routes to a clinical staff queue, not a dead end.
HIPAA compliance for AI chatbots requires: BAAs with all vendors processing PHI (including the LLM API provider -- Anthropic, OpenAI, and major cloud providers offer BAAs for healthcare use), encrypted data handling throughout the stack, audit logging of PHI access, minimum necessary PHI access (the chatbot accesses only what's needed for the interaction), and patient identity verification before accessing PHI. We design the architecture to meet these requirements from the start -- the chatbot never sends PHI to an AI provider without a BAA in place, and conversation logs containing PHI are stored in HIPAA-compliant infrastructure. We include HIPAA compliance documentation with every project.
We integrate with EHR systems that provide FHIR R4 APIs: Epic (via MyChart SMART on FHIR and Epic FHIR APIs), Cerner/Oracle Health (FHIR R4), Athenahealth, Allscripts, Kareo, and most modern EHRs with FHIR support. For EHRs with limited FHIR coverage, we can integrate with appointment scheduling via HL7 v2 messaging or proprietary APIs where available. The depth of integration depends on what the EHR's API supports -- appointment read/write, patient demographics, care plan data, and medication lists vary in availability by EHR. We confirm integration scope during scoping based on your specific EHR.
A focused healthcare chatbot -- appointment scheduling, intake collection, and FAQ automation with EHR read integration for patient identification -- typically runs $30,000--$70,000. A full healthcare AI chatbot with symptom triage, FHIR bidirectional integration, care plan support, and custom clinical content management typically runs $70,000--$150,000. Cost depends on EHR integration depth, clinical content scope, and the complexity of the triage and escalation logic. We scope every project before pricing it and include HIPAA compliance documentation.
Talk to us about your healthcare AI chatbot project.
Tell us the patient workflows you want to automate, your EHR system, and the clinical boundaries you need the chatbot to respect. We'll scope the right solution and give you a fixed cost.
