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Your Nurses Are Doing Work AI Should Handle

If you're running a health system where nurses spend 3 hours daily on phones instead of patients, your AI integration window is closing.

Your nursing staff spends 3 hours daily on scheduling, claims processing, and documentation. Your patients wait 20 minutes on hold to book a follow-up. Your admin team manually pulls insurance claims every Friday afternoon. We connect Claude to your Epic, Cerner, or Allscripts system so a nurse can say schedule a follow-up for room 412 with Dr. Patel in 2 weeks and it actually happens -- checks the calendar, finds a slot, books it, sends the patient a confirmation SMS.

8,600
Monthly Searches
AI for healthcare keywords
3hrs/day
Admin Time Saved
Per staff member
HIPAA
Fully Compliant
BAA included
95+
Lighthouse Score
Performance target
What Healthcare AI Integration Actually Does -- And What It Won't Touch

Your patient calls at 7 AM to reschedule. The AI picks up, checks your Epic calendar through a FHIR R4 connection, offers three slots based on provider availability and insurance pre-auth requirements, books the appointment, sends confirmation via SMS, and logs the interaction in your EHR audit trail. Your front desk never touched it. That's healthcare AI integration -- not a chatbot that sits beside your systems, but code that reads and writes directly into Epic, Cerner, Allscripts, your billing platform, and your scheduling workflows. It processes insurance claims by pulling patient records, cross-referencing CPT codes against payer rules, flagging denials before submission. It triages incoming messages using clinical decision trees your team defines. It generates visit notes from recorded consultations while your physician maintains eye contact with the patient. Every interaction is HIPAA-compliant: data encrypted in transit and at rest, BAAs signed with Supabase and Anthropic, zero persistent storage of PHI, audit logs on every AI touch. Your compliance officer gets documentation before deployment, not after something breaks.

What is holding your current website back?

AI should handle the paperwork so clinicians can focus on patients.

Nurses are burning roughly 3 hours every single day on scheduling and phone calls
Risk: That's clinical time -- time that should be spent with patients -- disappearing into administrative work that AI can handle in seconds. And it adds up fast across a full nursing staff.
Insurance claims pile up unprocessed for days -- sometimes weeks -- because your billing team is just overwhelmed
Risk: That backlog isn't just an inconvenience. It's a direct hit to cash flow and delayed reimbursements that compound into real financial problems for the practice.
Patients are sitting on hold for 20, sometimes 30 minutes just to book a follow-up
Risk: That's not a minor friction point. People hang up, get frustrated, and honestly -- they start looking at other providers. Patient satisfaction scores drop and you don't always see why until it's too late.
Clinical documentation is eating 45 minutes per patient encounter
Risk: Do that math across a full day of appointments and you've got physicians staying late, skipping breaks, and burning out fast. Documentation backlogs follow, and quality suffers.
Your EHR is sitting on years of patient data -- and it's basically unsearchable
Risk: Critical history is buried in unstructured notes that nobody has time to dig through. So clinicians make decisions without the full picture. That's a patient safety issue, not just an efficiency one.
You've probably already tried a chatbot
Risk: And it probably gave patients the same generic FAQ answers it gives everyone, because it couldn't actually touch your scheduling system or patient records. So patients stopped using it. That's not an AI problem -- it's an integration problem. And it's fixable.

How We Build This Right

Every safeguard, built in from Day 1.

AI Scheduling Assistant

Voice-activated appointment booking that's actually connected to your EHR calendar -- not a demo environment, your real calendar. A nurse says "schedule a follow-up" and the AI checks availability, books the slot, and fires off a patient confirmation via SMS or email. It works with Epic, Cerner, and Allscripts through FHIR API connections. No clicking through five screens. Just done.

Claims Processing AI

AI reads your unprocessed insurance claims, validates CPT codes, flags discrepancies, and generates submission-ready batches. It pulls directly from your billing system -- either on a set schedule or on demand. The real kicker is how many claim errors it catches before submission, which means fewer rejections and faster reimbursement.

Patient Triage Chatbot

A symptom assessment chatbot lives on your website or patient portal. It evaluates urgency, figures out the right care level, and routes the patient to the appropriate department. And it's not just making guesses -- there are clinical guardrails built in, plus escalation paths to human staff when anything falls outside defined parameters. Pretty straightforward in concept, but the implementation details matter enormously here.

Clinical Documentation AI

Voice-to-notes during consultations. The AI listens, generates structured clinical notes from the conversation, and formats them to match your specific EHR template requirements. Physician reviews, makes any edits, and approves. That's it. No more 45-minute documentation sessions after clinic hours.

Drug Interaction Checker

During prescribing workflows, AI queries your live formulary database and cross-references it against the patient's current medication list. Flags potential drug interactions, contraindications, and dosage concerns -- in real time, before the prescription goes out. It's not a replacement for clinical judgment. But it's a safety net that doesn't take breaks.

Patient Communication

Appointment reminders, post-visit follow-up instructions, care plan summaries -- all automated, all sent via SMS and email. But here's what makes it useful rather than just convenient: the AI personalizes each message based on the patient's actual records and treatment history. Not a mail merge. Real personalization.

What We Build

Purpose-built features for your industry.

Connects via FHIR R4 APIs to Epic, Cerner, and Allscripts with read-write access to scheduling, billing, and clinical records

Your nurses reclaim 3 hours per day from phone scheduling and insurance verification calls

Processes voice commands through ElevenLabs so your clinicians stop typing during patient encounters

Your billing team processes claims in minutes instead of letting backlogs compound for weeks

Encrypts all patient data in transit and at rest with signed BAAs from every vendor in the stack

Your patients book appointments in under 90 seconds without sitting on hold until they hang up frustrated

Logs every AI interaction with PHI in tamper-proof audit trails your compliance team can export

Your physicians document encounters in real time using voice instead of staying late to finish notes

Flags clinical recommendations outside defined parameters and escalates to physician review automatically

Your clinicians surface buried patient history from unstructured EHR notes during the actual consultation

Deploys alongside your existing EHR without replacing workflows your staff already knows

Your practice hits ROI within the first month through measurable time savings tracked in your analytics dashboard

Built on a Modern, Secure Stack

Claude APIFHIR APIElevenLabsSupabaseVercelTwiliopgvector

Our Development Process

From discovery to launch. Quality at every step.

01

Clinical Workflow Audit

Week 1

First, we shadow your staff for a week. Every admin task, every phone call, every manual process -- we map it all. Then we identify where AI will have the highest impact, based on actual time data. Not assumptions. Not demos. What's really happening in your building.

02

HIPAA Architecture

Week 2

Before any development starts, we design the full integration architecture -- encryption, access controls, BAAs, audit logging. Then a compliance review. Legal and IT both sign off before we write a line of code. This step takes longer than clients expect, but it's the reason everything downstream goes smoothly.

03

EHR Connection

Week 3-5

We build the FHIR API connections to your EHR and test everything against anonymized data first. Nobody touches production systems until we've validated behavior in a safe environment. That's non-negotiable on our end.

04

AI Training and Testing

Week 6-8

Generic AI doesn't work in clinical settings. So we configure everything to your specific workflows, your terminology, your protocols. Then real staff run real scenarios -- not scripted demos -- before we call anything done.

05

Phased Rollout

Week 9-12

We don't flip a switch and walk away. We start with one department, measure results for 60 days, optimize based on what we learn, and then expand. Phased rollout keeps risk low and gives staff time to actually get comfortable with the tools.

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Frequently Asked Questions

Yes -- and here's specifically how. All data encrypted. BAAs in place with every hosting provider we use. AI processes patient data in memory without writing anything to persistent storage. Full audit logs on every interaction. We've built HIPAA-compliant systems for hospitals and clinics before, and we can provide compliance documentation for your legal and IT teams to review.
Epic, Cerner, and Allscripts through FHIR R4 are the main three. But we also connect to practice management systems, billing platforms, and custom healthcare databases. Honestly, if your system has an API, we can connect AI to it. That covers most of what's out there.
Yes -- and it's more specific than people expect. A nurse says "schedule a follow-up for the patient in room 412 with Dr. Patel in two weeks." The AI checks Dr. Patel's actual calendar, finds open slots, books it, and sends the patient a confirmation SMS. All of that happens in your real scheduling system. Not a prototype. Not a simulation.
An AI scheduling assistant connected to your EHR runs $30,000 to $50,000. The full suite -- claims processing, triage chatbot, clinical documentation, the whole thing -- is $80,000 to $150,000. And that's against a system that saves 15 or more hours per week per staff member. The math works out pretty quickly.
A single workflow like scheduling takes 4 to 6 weeks. The full healthcare AI suite is 10 to 12 weeks -- that includes HIPAA compliance setup, EHR integration work, staff configuration, and a phased rollout starting with one department. Rushing the compliance piece is how projects go sideways, so we don't.
Patient data never leaves your infrastructure. When the Claude API processes a query, it happens in memory -- patient information isn't stored anywhere. All connections are encrypted. All access is logged. And we'll hand your legal and IT teams full compliance documentation so they can verify everything themselves rather than just taking our word for it.
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