AI for Healthcare

We build secure, auditable AI employees that handle the repetitive administrative work overwhelming your healthcare practice. This allows your clinical and operational teams to focus on patient care, not paperwork.

Where AI actually moves the needle in healthcare

The core challenge in healthcare operations is not a lack of skilled people, but a crushing volume of administrative tasks that do not require a clinical license. These tasks create significant friction, delay patient care, and directly contribute to staff burnout. We see this manifest as backlogs in patient intake, revenue cycle bottlenecks, and clinicians spending hours after their shifts completing documentation.

Prior authorization is a prime example. A dedicated staff member can spend their entire day navigating payer portals, filling out forms, and waiting on hold, only to have a request denied due to a minor documentation error. This administrative drag delays necessary procedures, frustrates patients, and puts revenue at risk. The operational pain is a direct result of manual, repetitive work that is a perfect fit for automation.

Similarly, patient scheduling and referral management are fraught with manual communication loops. A single referral can involve multiple phone calls and faxes to transmit records, confirm receipt, and schedule an appointment. This process is slow, prone to error, and often results in lost referrals and care gaps. The staffing required to manage this process at scale is substantial, straining operational margins.

Finally, the burden of clinical documentation is a well-documented driver of physician burnout. Clinicians are forced to become data entry clerks, typing into the EHR during and after patient encounters. This detracts from patient interaction and extends the workday. AI can help reclaim this time by handling the initial drafting of notes, allowing clinicians to simply review and approve.

Six AI employees we deploy for healthcare teams

• Prior Auth Specialist — Manages the end-to-end prior authorization lifecycle. This AI employee monitors the EHR for new orders requiring authorization, gathers necessary clinical documentation, submits requests through payer portals, and provides status updates directly in the patient's chart. We integrate with systems like Epic, Cerner, and Athenahealth, typically reducing authorization turnaround time by 30-50%.
• Intake Coordinator — Automates patient registration and data collection. It sends secure digital intake forms to patients via SMS or email, validates insurance information against clearinghouses, and enters the structured data into your practice management system. This reduces front-desk wait times and improves the accuracy of demographic and insurance data from day one.
• Clinical Scribe Assistant — Drafts encounter notes from ambient conversation. Using secure, HIPAA-compliant speech-to-text models, this AI employee listens to the patient-clinician conversation and generates a structured SOAP note draft within the EHR. The clinician then reviews, edits, and signs off. In our engagements, this saves physicians an average of 5-10 hours per week on documentation.
• Referral Coordinator — Processes inbound and outbound referrals. For outbound referrals, it packages and sends the required chart notes and imaging to the receiving provider via secure channels. For inbound, it creates a new patient shell in the EHR, flags missing records, and initiates the scheduling process. This helps close referral loops faster and reduces patient leakage.
• Billing & Coding Assistant — Suggests medical codes based on clinical documentation. This AI reviews the final encounter note and suggests relevant CPT and ICD-10 codes, highlighting any documentation deficiencies that could lead to a denial. It acts as a pre-check for your human coders, integrating with your billing software to improve coding accuracy and reduce the claim denial rate.
• Patient Engagement Agent — Automates routine patient communication. It handles appointment reminders, post-visit follow-up instructions, and care gap notifications (e.g., "You are due for a flu shot"). We deploy this using platforms like Twilio for SMS and integrate with your patient portal, which typically reduces no-show rates by 15-25%.

A 90-day rollout plan

1. Weeks 1-2: Discovery and Workflow Mapping. Our first step is to understand your specific operational environment. We conduct focused workshops with your administrative and clinical teams to map one or two high-impact workflows, such as prior authorization or patient intake. We analyze your existing systems (EHR, PM), document process variations, and define clear success metrics. This phase culminates in a detailed Statement of Work and a finalized pilot plan.
2. Weeks 3-6: First AI Employee Deployed in Pilot. We configure and deploy the first AI employee for the initial workflow identified in discovery. This involves setting up secure API connections to your EHR and other systems within a controlled environment. The AI begins handling a small percentage of live tasks, with every action logged and reviewed by your team and ours. This allows us to fine-tune the models and logic based on real-world performance.
3. Weeks 7-10: Expand First Workflow and Add Second. Once the first AI employee meets the agreed-upon accuracy and efficiency KPIs, we scale its workload to cover the entire department or process. Concurrently, we begin development and pilot deployment of the second AI employee for the next priority workflow. We focus on building deeper integrations, such as writing status updates back into custom fields in Salesforce Health Cloud or your EHR.
4. Weeks 11-13: Scale, Governance, and Handover. By the end of the quarter, two AI-powered workflows are fully operational, handling a significant volume of tasks. We work with your team to establish long-term governance, including monitoring dashboards, escalation protocols for exceptions, and audit procedures. We provide comprehensive training and documentation so your team can manage the AI employees and monitor their performance independently.

What good ROI looks like

The return on investment from deploying AI employees is measured in saved hours, direct cost reduction, and improved revenue velocity. For administrative roles, we typically see a 40-70% reduction in the time required to complete tasks like processing a referral or submitting a prior authorization. This frees up staff to focus on more complex, patient-facing responsibilities, often allowing a practice to handle increased patient volume without increasing administrative headcount.

From a direct cost perspective, the ROI is clear. An automated task, such as verifying insurance eligibility, can have its cost per transaction reduced by over 80% compared to the fully-loaded cost of a human employee. For clinical staff, the value is in time reclamation. Saving a physician 8 hours of documentation work per week is not a direct cost saving, but it's a powerful tool against burnout and can create capacity for two to three additional patient visits per day.

Faster administrative processes also accelerate the revenue cycle. When prior authorizations are approved days earlier and claims are submitted with higher coding accuracy, cash flow improves. We typically see a 5-10% reduction in average days in A/R for the processes we automate. This improvement in revenue velocity, combined with reduced operational costs, delivers a tangible financial return within months of deployment.

Compliance, data, and risk

We build our healthcare solutions with a HIPAA-first mindset. All processing of Protected Health Information (PHI) occurs within a secure, HIPAA-compliant environment, which can be your own private cloud or a dedicated Virtual Private Cloud (VPC) on a major provider like AWS or Azure. We sign a Business Associate Agreement (BAA) for every engagement, formally accepting our responsibility to safeguard PHI.

Our architecture is designed for data minimization and security. Where possible, our models are trained on de-identified data. For live operations, we use sophisticated PII/PHI redaction techniques to ensure sensitive data is not unnecessarily exposed or logged. Every action taken by an AI employee is captured in an immutable audit log, providing full transparency for compliance reviews. This log details what data was accessed, what action was taken, and which human user reviewed or approved the step.

We mitigate operational and clinical risk by designing human-in-the-loop (HITL) workflows. The AI is not making autonomous clinical decisions. It drafts a note for a physician to review, suggests a code for a biller to confirm, or flags an authorization for a specialist to handle. These HITL checkpoints ensure that a qualified human makes the final judgment call on any sensitive or complex task, combining the efficiency of automation with the expertise and oversight of your team.

Common objections we hear

• Our workflows and EHR are too customized. We expect customization. Our discovery process is designed to map your specific fields, rules, and exceptions, and we build integrations using a combination of standard APIs (like FHIR and HL7) and custom adapters for non-standard systems.
• This will replace our administrative staff. Our goal is augmentation, not replacement. We automate the most repetitive, low-value tasks, which allows your skilled staff to operate at the top of their license and focus on complex cases and direct patient interaction.
• AI makes mistakes that could create patient safety issues. We scope our AI employees to administrative and documentation tasks, not clinical diagnosis or treatment planning. Furthermore, every workflow has built-in human review points for quality assurance before any action impacts patient care or billing.
• The implementation process will be too disruptive for our busy practice. We use a phased, pilot-based approach. We start with one workflow in a limited capacity, proving the value and refining the process with a small group of users before scaling, which minimizes disruption to your daily operations.

Frequently asked questions

How does AI work with our existing EHR?

We connect to your EHR (e.g., Epic, Cerner, Athenahealth) through secure, standard APIs whenever possible. For systems without modern APIs, we can build custom integrations or use secure robotic process automation (RPA) to interact with the user interface just as a human would. All integrations are read-only by default, and write-back permissions are tightly controlled and logged.

What happens if the AI encounters a case it can't handle?

Our systems are designed with clear exception-handling rules. If an AI employee encounters a situation outside its training (e.g., a new insurance form, an unusual clinical note), it automatically escalates the task to a designated human team member via Slack, email, or a task queue within your existing software. The task includes all context, so your team can resolve it efficiently.

Is our patient data secure?

Yes. We operate under a strict Business Associate Agreement (BAA). All patient data is encrypted in transit and at rest, and processed within a HIPAA-compliant environment. We do not use your PHI to train models for other customers, and we provide full audit trails of all data access and actions taken by the AI.

How much training does my team need?

Minimal training is required. Because our AI employees work within your existing software, your team's primary new task is managing the exceptions queue. We provide short, role-specific training sessions and detailed documentation on how to review AI-assisted work and handle escalations.

What is the pricing model?

Our pricing is typically a combination of a one-time implementation fee and a monthly subscription. The subscription fee is based on the number of AI employees deployed and the volume of tasks they handle. This model ensures our costs scale with the value and ROI you receive.