AI agents for
healthcare organizations.
Automate patient intake, deploy ambient clinical documentation, accelerate prior authorizations, and optimize scheduling — with HIPAA-compliant architecture, BAA coverage, and physician-approved human-in-the-loop controls.
Where healthcare AI agents deliver results.
Four workflows where we consistently see measurable impact within the first 90 days of deployment.
Patient Intake Automation
Before
Patients fill out paper forms in the waiting room. Front desk staff manually enters demographics, insurance details, and medical history into the EHR. Errors propagate downstream into billing and clinical records. Average check-in takes 15 minutes.
After
A digital intake agent sends pre-visit forms to patients 48 hours before the appointment. It verifies insurance eligibility in real-time, flags discrepancies against existing records, and pushes validated data directly into the EHR — so the patient walks in with their chart already current.
75% reduction in check-in time
Ambient Clinical Documentation
Before
Physicians spend 2 hours per day on documentation after clinic hours — the so-called 'pajama time.' Notes are entered retrospectively, missing nuance from the encounter. Burnout rates climb. Patient face-time suffers.
After
An ambient AI agent listens to the patient-physician conversation, generates a structured SOAP note in real-time, maps diagnoses to ICD-10 codes, and presents the draft for physician attestation before the next patient walks in.
90 min/day saved per physician
Prior Authorization Agent
Before
Clinical staff spend 45 minutes per prior auth request — gathering clinical documentation, filling payer-specific forms, faxing, calling, and following up. Denials require additional rounds. Patients wait days or weeks for treatment approval.
After
A prior auth agent extracts relevant clinical data from the EHR, matches it to payer-specific criteria, generates the submission package, and tracks the request through to determination — escalating to staff only when a human appeal is required.
60% faster auth turnaround
Appointment Scheduling Optimization
Before
Schedulers manually manage provider templates, patient preferences, and resource constraints. No-show rates hover at 15-20%. Overbooking causes wait time complaints. Underbooking leaves revenue on the table.
After
A scheduling agent predicts no-show probability per patient, dynamically adjusts overbooking levels, sends smart reminders calibrated to patient engagement history, and fills cancellations from the waitlist in minutes — not hours.
40% reduction in no-shows
Built for healthcare leaders who need outcomes.
Chief Technology Officers at health systems
You are responsible for EHR infrastructure, interoperability, and the technical feasibility of AI initiatives across a multi-facility health system. You need HIPAA-compliant AI agents that integrate with your existing Epic or Cerner environment without creating shadow IT.
Chief Medical Information Officers (CMIOs)
You sit at the intersection of clinical practice and technology. You need AI tools that physicians will actually use — ones that reduce documentation burden, improve clinical decision support, and fit into existing workflows without adding friction.
VP of Operations at hospitals and clinics
You are measured on throughput, patient satisfaction, and operational cost per encounter. AI agents that automate prior authorization, optimize scheduling, and streamline intake directly impact your KPIs without requiring additional FTEs.
Practice managers at multi-provider groups
You manage the day-to-day operations of a growing practice — scheduling, front desk workflows, insurance verification, and patient communications. You need automation that works with your existing PM system and does not require a dedicated IT team to maintain.
From risk assessment to production agent.
HIPAA Risk Assessment
We map every PHI touchpoint in the target workflow, classify data sensitivity levels, identify BAA requirements with all third-party services, and document the minimum necessary data access patterns before writing a single line of code.
PHI-Safe Architecture
We design the agent architecture with encryption at rest and in transit, role-based access controls, audit logging, and EHR integration patterns — all reviewed with your compliance and security teams before development begins.
Clinical Pilot
We deploy to a controlled clinical environment — one department, one workflow, limited patient volume. We measure accuracy, clinician satisfaction, and patient outcomes with your quality team before expanding organization-wide.
Monitoring & Compliance Reporting
Production agents run with real-time compliance dashboards, PHI access audit trails, clinical accuracy metrics, and automated alerts for anomalous behavior. Your compliance team gets the reports they need for HIPAA audits.
Questions about healthcare AI agents.
How do you ensure HIPAA compliance and will you sign a BAA?
HIPAA compliance is embedded into our architecture from day one — it is not an afterthought. Every AI agent that touches PHI is built with encryption at rest and in transit, role-based access controls, comprehensive audit logging, and minimum necessary data access patterns. We sign a Business Associate Agreement (BAA) before any development begins and we conduct a formal risk assessment aligned with the HIPAA Security Rule before deploying to production. Our cloud infrastructure runs on HIPAA-eligible services within AWS or Azure with BAA coverage at the infrastructure layer as well.
Can your AI agents integrate with Epic, Cerner, or other EHR systems?
Yes. We build integrations using FHIR R4 APIs, HL7v2 interfaces, and vendor-specific SDKs. For Epic, we work through the App Orchard marketplace and FHIR endpoints. For Oracle Health (Cerner), we use the Millennium platform APIs and CDS Hooks. For smaller EHR systems like athenahealth, eClinicalWorks, or NextGen, we use their respective API programs or build HL7 ADT/ORM interface engines. We also integrate with practice management systems, clearinghouses, and ancillary systems like PACS for radiology workflows.
How do you ensure clinical accuracy in AI-generated documentation?
Clinical accuracy is non-negotiable. Our ambient documentation agents use medical-grade language models fine-tuned on clinical encounter data. Every generated note goes through a structured validation pipeline: medical terminology verification against SNOMED CT and ICD-10 code sets, drug interaction cross-referencing, and consistency checks against the patient's problem list and medication history. The physician reviews and attests to the final note before it is committed to the chart. We measure hallucination rates, omission rates, and coding accuracy in every pilot and maintain these metrics in production dashboards.
What does physician and clinical staff adoption typically look like?
Physician adoption is the hardest part of healthcare AI and we plan for it explicitly. We start with administrative agents that remove burden without changing clinical workflows — prior authorization processing, appointment scheduling, intake form digitization. Physicians see their staff getting hours back and their own inbox shrinking before we introduce clinical-facing tools. For ambient documentation, we pilot with physician champions who are already frustrated with documentation burden. When those champions report saving 60-90 minutes per day, peer adoption follows. We never deploy clinical AI without physician sign-off on the workflow design.
How do you handle patient consent for AI-processed health data?
Patient consent requirements depend on the use case and applicable state law. For treatment-related AI (documentation, clinical decision support), HIPAA's treatment exception generally applies — but we still recommend transparent patient communication. For non-treatment uses like population health outreach or research, we build consent management workflows into the agent architecture. We support granular opt-in/opt-out preferences stored in the EHR, dynamic consent capture during patient intake, and automated consent verification before any agent processes PHI for secondary purposes. We also track state-specific regulations — California CMIA, New York SHIELD, Texas HB 300 — and configure the consent engine accordingly.
Healthcare AI expertise — not generic automation vendors
We build AI agents specifically for healthcare workflows — prior auth, clinical documentation, patient engagement — with HIPAA compliance designed into the architecture from day one. You contract with a US LLC (Florida), communicate in your timezone, and get senior AI engineers with genuine healthcare domain knowledge at 40-60% less than US-only rates through our LATAM delivery capacity. Every engagement starts with a signed BAA and a formal risk assessment.
HIPAA-compliant by design
BAA signed before development begins, PHI architecture reviewed with your compliance team
EHR integration experience
Epic, Oracle Health (Cerner), athenahealth, eClinicalWorks — we know these systems
Ready to reduce administrative burden on your clinical staff?
Tell us which workflow is consuming the most staff time — prior authorizations, clinical documentation, patient intake, or scheduling. We'll map the agent opportunity and give you an honest assessment before you commit.