AI system for remote patient monitoring
- 150+
- patients under monitoring in 12 weeks
- 20%
- reduction in clinical decision-making time
Healthcare AI Chatbot Development
A healthcare AI chatbot needs clinical scope control, not just chatbot infrastructure.
Generic chatbot platforms can answer patient questions, but without scope controls and escalation design they can give clinically inappropriate responses that create liability and erode patient trust. 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.
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
Bring the problem, the current workflow, or the existing code. We reply with a practical next step within one business day.
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The brief
Start with what is not working.
Good software decisions begin with the constraint, not a list of features or a preferred technology.
01
Clinical staff spending significant time on patient FAQ calls, appointment rescheduling, and intake data collection that AI could handle consistently?
02
Generic chatbot platforms not meeting HIPAA requirements or unable to integrate with your EHR for appointment and patient data access?
Plain answer
RaftLabs builds HIPAA-compliant healthcare AI chatbots for patient intake, symptom collection, appointment scheduling, and clinical FAQ automation. Each chatbot integrates with your EHR via FHIR, handles PHI only under a signed BAA with full audit logging, and escalates anything clinical to staff. Launch a scoped v1 in 8-14 weeks at a fixed cost, then expand.
What to remember
- Clinical safety guardrails are non-negotiable: the chatbot never diagnoses, never recommends changing a prescription, and always closes with a recommendation to seek professional consultation.
- Urgency flagging applies rule-based clinical safety guardrails over collected symptoms, escalating time-sensitive patterns (chest pain with dyspnoea, stroke signs) immediately with full structured context handed to the clinician.
- No PHI reaches any system without a valid BAA in place, and inference-only API access (never fine-tuning) means patient conversations never train the model.
- A first workflow, say appointment scheduling or intake with EHR read integration, starts around $30,000; a full build with symptom triage and bidirectional FHIR grows toward $150,000 as you expand scope.
The front desk answers the same five questions all day. The chatbot should answer four of them.
A patient messages the practice at 9pm: "Can I move Thursday's appointment, and do I need to fast before my blood draw?" A generic chatbot answers both, and guesses at the second one. The guess is wrong, and now a clinically inappropriate response is sitting in your patient's inbox as liability.
A scoped chatbot reschedules the appointment against the EHR, and hands the fasting question to a nurse with the patient's context already attached. It handles what it was trained to handle, and escalates the rest.
That boundary is the product. The chat window is the easy part.
Generic chatbot platforms can answer patient questions. Without scope controls and escalation logic, they answer questions they were never meant to touch, and a clinically inappropriate reply becomes liability and lost patient trust. We build healthcare chatbots with scope-limited response design: the assistant handles appointment queries, intake collection, care plan FAQ, and medication reminders, then escalates to clinical staff for anything outside that boundary. Clear escalation matters as much as the conversation itself.
Patient expectations have shifted toward self-service. Accenture's Digital Health Consumer research found that most patients want digital options for routine tasks like scheduling, refills, and questions, much of it arriving outside clinic hours.
RaftLabs has shipped production software since 2015, including HIPAA-compliant healthcare platforms. The architecture is HIPAA-compliant by design: EHR integration via FHIR, round-the-clock coverage, and no PHI reaching any system without a signed BAA. The team that scopes your EHR and clinical workflows is the team that builds it, with a fixed cost locked in writing before development starts.
Proof
- Since 2015
- shipping production software, including HIPAA-compliant healthcare platforms
- RaftLabs delivery record
- 4.9/5
- average client rating across delivered projects
- Clutch, verified reviews
- 24/7
- HIPAA-compliant patient support via FHIR EHR integration, no PHI without a signed BAA
- Every healthcare chatbot build
A scoped chatbot pays off when the volume is repeatable and the boundaries are clinical.
Everything on the left should already be true for your practice. Even one thing on the right, and a generic FAQ bot is the smarter first step.
A fit
01
Clinical staff spending significant time on patient FAQ calls, appointment rescheduling, and intake collection that follows the same logic every time.
02
An EHR with FHIR access (Epic, Cerner/Oracle Health, Athenahealth, Allscripts, or similar) to integrate against for patient identification and appointment data.
03
A clinical team ready to define scope, triage rules, and escalation logic, and infrastructure that supports a signed BAA.
Not a fit
01
You want the chatbot to diagnose, recommend prescription changes, or give medical advice beyond approved content.
02
No EHR or booking system to integrate with, and no plan to add one.
03
You need a generic FAQ responder with no PHI handling, HIPAA requirements, or clinical escalation.
What we build
Clinical scope control, not just chatbot infrastructure
- 01Patient intake automationMulti-turn conversational intake maps symptoms to ICD-10 categories, with medical NER extracting clinical entities before submission to the EHR as a FHIR QuestionnaireResponse. Built on LangGraph with BioBERT for clinical entity extraction.
- 02Symptom collection and triage supportClinical decision logic modelled as a state machine flags time-sensitive patterns for immediate escalation, with the full structured symptom context handed off to the clinician.
- 03Appointment scheduling and managementSMART on FHIR-authenticated booking against Slot and Appointment resources on FHIR R4, with automated reminders and personalised pre-appointment preparation instructions.
- 04Clinical FAQ and care plan supportRAG over an approved clinical content library answers within scope only, escalating rather than generating a speculative answer when a question falls outside it.
- 05HIPAA-compliant infrastructureBAAs with every infrastructure provider, inference-only LLM access with no PHI in training data, and full audit logging of every PHI access event.
- 06EHR integration and data accessFHIR R4 resource types (Patient, Appointment, CarePlan, MedicationRequest) with SMART on FHIR OAuth 2.0 scoping access to only what each interaction needs, across Epic, Cerner, and most modern EHRs.
Have a 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.
How it works
From scope to live healthcare chatbot
- Week 101
Workflow and EHR scoping
We map the patient workflows you want to automate, your EHR system, and clinical boundaries. You leave week 1 with a written scope document and a fixed-price quote.
- Weeks 2-402
Clinical guardrail and escalation design
Triage rules and escalation logic defined with your clinical team and reviewed by a clinician before build.
- Weeks 5-1103
Build and integrate
Intake flows, FHIR integration, and HIPAA-compliant infrastructure built in parallel, tested against real clinical scenarios.
- Final 2-3 weeks04
Launch and clinical review
Clinical team reviews escalation logic and audit trail before full production rollout.
The closest proof we can point to is neighbouring healthcare AI work: a HIPAA-compliant remote patient monitoring platform we built for a US healthcare client. It shares the parts that matter for a chatbot, FHIR EHR integration, PHI handling under a BAA, and clinical workflow design.
Proof
Related healthcare AI work
Where you land in that range depends on scope, not negotiation:
- Focused chatbot, $30,000-$70,000
- Appointment scheduling, intake collection, and FAQ automation with EHR read integration.
- Full chatbot, $70,000-$150,000
- Everything in the focused build, plus symptom triage, bidirectional FHIR integration, and care plan support.
What it costs
HIPAA-compliant chatbot, starting at $30,000.
Scope-limited response design, EHR integration via FHIR, clinical escalation, and full PHI audit logging, launched as a validated v1 in 8-14 weeks.
Most practices start with a single, well-defined use case rather than a do-everything bot. Once it's live and trusted, we expand the scope to cover more of the patient journey.
Starting investment
Starts at $30,000
Launch a validated v1 in 8-14 weeks. Start with one use case, like appointment triage or symptom intake, and expand once it's handling real conversations safely. No PHI reaches any system without a signed BAA.
No hourly billing
Once we scope your first use case, that price is locked in writing, so there's no hourly billing and no invoice surprises. A scope change is a priced change request, agreed before work begins.
Clinician-reviewed
Triage rules are defined with your clinical team and reviewed by a clinician before build, and no PHI reaches any system without a valid BAA in place.
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Read moreFrequently asked questions
Chatbots handle appointment scheduling, administrative FAQ, structured intake collection, approved care plan FAQ, medication reminders, and post-visit check-ins. Clinical staff always handle advice beyond approved content, any symptom pattern flagged as potentially urgent, diagnosis or treatment questions, and any patient expressing distress or safety concerns.
HIPAA compliance requires BAAs with all vendors processing PHI including the LLM provider, encrypted handling throughout the stack, audit logging of PHI access, minimum necessary access, and patient identity verification before accessing PHI. The chatbot never sends PHI to a provider without a BAA in place.
We integrate with EHR systems providing FHIR R4 APIs: Epic, Cerner/Oracle Health, Athenahealth, Allscripts, Kareo, and most modern EHRs. For limited FHIR coverage, we integrate via HL7 v2 messaging or proprietary APIs where available.
A focused chatbot covering appointment scheduling, intake collection, and FAQ automation with EHR read integration typically runs $30,000-$70,000. A full chatbot with symptom triage, bidirectional FHIR integration, and care plan support typically runs $70,000-$150,000.
Work with us
Tell us where the work is stuck.
Bring the rough workflow, half-built product, or messy brief. We will map the smallest useful first move, then send scope, timeline, and price in plain English.
- Scope and cost agreed before work starts. No surprises. No obligation.
- Working prototype within 3 weeks of kickoff.
- Pay by milestone. You see progress before each invoice.
- 60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
- All conversations are NDA-protected.
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