Healthcare AI automation for the reading and writing around the visit.
The AI drafts the brief, the packet or the letter. A clinician reviews it before it counts.
Providers and billing staff spend hours reading: intake questionnaires, outside records, chart notes, payer criteria. Then they write: summaries, prior authorization justifications, letters. We build AI that does the first pass on that reading and writing, shows where each statement came from, and leaves every clinical and coverage decision with your people.
- Free
- AI audit before you commit to anything
- BAA
- Signed whenever PHI is in scope
- Clinician review
- On every document the AI drafts
The reading and writing around each visit lands on your clinicians
Pre-visit reading that runs past clinic hours
A new patient arrives with a long intake questionnaire, scored screening tools and a stack of outside records. The provider reads all of it to find the few details that will shape the visit, often after the last patient has gone home.
Prior authorizations built from scattered notes
The payer wants the diagnosis, the dates of conservative treatment that failed and the clinical findings that meet its criteria. Your billing staff dig through months of chart notes to find them, then rewrite them into the payer's format.
Letters and summaries written from scratch
Letters of medical necessity, referral letters and plain-language visit summaries all restate what is already in the chart. Each one is written by hand, and the backlog grows on the busiest weeks.
What we build for clinics and medical practices
Each of these is a real engagement shape. Open one to see how it works, what it needs from you, and where a person stays in the loop.
Any figures are targets we scope towards, not guarantees. What you actually get depends on your volume, your systems, and how much stays under human review.
Provider-ready brief from intake and records
Providers prepare for new-patient and evaluation visits by reading long questionnaires, scoring screening instruments and skimming outside records.
Provider-ready brief from intake and records
Providers prepare for new-patient and evaluation visits by reading long questionnaires, scoring screening instruments and skimming outside records.Validated screening instruments are scored in code, using their published scoring rules. The AI then organizes the questionnaire answers and records into a short brief for the provider, with each point tied to the answer or page it came from, and suggests areas to explore in the visit.
How it works
- 01Read the completed intake questionnaire from your patient portal or intake tool
- 02Score standardized instruments in code so the numbers are exact and checkable
- 03Summarize narrative answers and attached records into a brief in your template
- 04Link each statement in the brief back to its source answer or document
- 05Deliver the brief to the provider before the appointment for review
Where a person stays in the loop
The brief organizes what the patient and the records say. It contains no diagnosis and no clinical conclusion, and the provider reads it before the visit.
- Every brief states that it is a preparation aid, not a determination
- Provider reviews the brief and the source documents it cites
- If the AI step fails, the output says so instead of looking normal
What it needs from you
- Your intake questionnaire and the instruments it includes
- API or export access to your intake tool or patient portal
- A sample brief, or a provider willing to shape one with us
Common questions
- Is the patient data de-identified before the AI sees it?
- Direct identifiers can be stripped before anything is sent for processing, but free-text answers may still contain names, employers or dates a patient chose to write. That makes it a limited data set rather than de-identified data, and we describe it that way. It is one reason we work under a BAA.
Typical build: 3 to 4 weeks·Aim: Providers walk in knowing what matters for this patient
Talk through this oneEligibility summaries and prior authorization packets
Staff read benefit responses line by line and assemble prior authorization justifications by searching chart notes for the details each payer asks for.
Eligibility summaries and prior authorization packets
Staff read benefit responses line by line and assemble prior authorization justifications by searching chart notes for the details each payer asks for.The AI reads the eligibility response and summarizes what applies to the scheduled service. For a prior authorization, it compares the chart against the payer's criteria checklist, pulls the supporting notes into a draft packet and lists what is missing. Your staff review the packet and submit it.
How it works
- 01Pull the eligibility response from your clearinghouse or practice management system
- 02Summarize coverage, cost share and authorization requirements for the scheduled service
- 03Match chart notes, diagnoses and prior treatments against the payer's criteria
- 04Draft the packet with each criterion linked to the note that supports it
- 05Flag criteria with no supporting documentation for staff to resolve
Where a person stays in the loop
The AI prepares the packet. A billing or clinical staff member decides whether it is ready and submits it through your usual channel.
- Nothing is submitted to a payer automatically
- Unsupported criteria are listed, never filled in
- Clinical justification language is approved by the ordering provider
What it needs from you
- EHR access to the relevant chart notes, by API or export
- Eligibility data from your clearinghouse or practice management system
- The payer criteria or forms your team works from today
Typical build: 3 to 4 weeks·Aim: Packets that show their gaps before submission
Talk through this oneDocumentation drafted from structured notes
Letters of medical necessity, referral letters and patient-facing summaries repeat what the chart already says, and each one is written by hand.
Documentation drafted from structured notes
Letters of medical necessity, referral letters and patient-facing summaries repeat what the chart already says, and each one is written by hand.The AI drafts the document from the structured notes and findings already in the chart, in your templates and voice. The clinician edits and signs it. A plain-language version can be drafted for the patient from the same notes.
How it works
- 01Collect your current letter and summary templates, with good past examples
- 02Pull the relevant structured notes and findings for the patient
- 03Draft the document and mark any statement the notes do not support
- 04Send the draft to the clinician to edit and sign
Where a person stays in the loop
Drafts are drafts. Nothing goes to a payer, a referring office or a patient until the clinician has edited and signed it.
- Clinician signs every outbound document
- Statements without a source in the notes are flagged in the draft
What it needs from you
- Your letter and summary templates
- EHR note access by API or export
Typical build: 2 to 3 weeks·Aim: A shorter documentation backlog
Talk through this oneStaff answers from your own policies
Front desk and billing staff interrupt the office manager with the same questions about payer rules, cancellation policy and internal procedures.
Staff answers from your own policies
Front desk and billing staff interrupt the office manager with the same questions about payer rules, cancellation policy and internal procedures.Staff ask a question in plain language and get an answer drawn from your practice's own policy documents and payer notes, with a link to the source. When the documents do not answer it, the assistant says so and points to the person who owns that topic.
How it works
- 01Gather your policy manual, payer notes and procedure documents
- 02Index them in your own cloud account
- 03Answer staff questions with a citation to the source document
- 04Log unanswered questions so the policy owner can fill the gaps
What it needs from you
- Your policy and procedure documents, in any common format
- A named owner for each policy area
Typical build: 2 to 3 weeks·Aim: Policy answers that match the written policy
Talk through this oneBuilt inside your systems, not beside them.
We work in your cloud, using your tools, under least-privilege access. We never train models on your data, and you keep the source code.
BAA when PHI is in scope
We sign a Business Associate Agreement before touching protected health information.
Minimum necessary data
Direct identifiers are stripped where the task allows, and we say plainly when a payload is a limited data set rather than de-identified.
No training on your data
Patient data is used to do the task and is never used to train models.
Audit trail
Every AI output, edit and approval is logged with who reviewed it.
Systems we build around
- Athenahealth
- eClinicalWorks
- DrChrono
- Epic (via vendor programs)
- IntakeQ
- Tebra (formerly Kareo)
- AdvancedMD
- Availity
- Microsoft 365
These are systems clinics commonly ask about, not a list of existing integrations. We connect where your system offers an API, an interface or a reliable export, and confirm what your plan and contract allow during scoping.
Questions we get
What is healthcare AI automation?
Healthcare AI automation is software that reads and drafts the documents around patient care so clinicians and staff review instead of compile. Examples are summarizing an intake questionnaire into a provider brief, assembling a prior authorization packet from chart notes, and drafting a letter of medical necessity. A person reviews every output, and the software makes no clinical decision.
What can AI automate beyond basic workflow steps in a healthcare setting?
AI can take on work that needs reading and judgement, which simple workflow tools cannot. Workflow automation moves data between systems: a form into the EHR, a reminder from the schedule. AI automation reads unstructured material and produces something new from it, such as a pre-visit summary, a list of payer criteria met and missing, a drafted letter, or an answer sourced from your policy manual. Both are often useful, and we usually start with whichever costs your team the most time.
Is healthcare AI automation HIPAA compliant?
Healthcare AI automation software can be built to support HIPAA compliance, and that is how we build ours. When PHI is in scope we sign a BAA, run on infrastructure that offers its own BAA, send only the data each task needs, encrypt data in transit and at rest, and log every access. We are precise about de-identification: if free-text fields still go to the model, we call it a limited data set. Compliance also depends on how your practice uses the system, so we document responsibilities with you.
Does it integrate with EHR/EMR and billing systems?
Usually, through whatever access your systems allow. We check whether your EHR, practice management system and clearinghouse offer an API, an interface engine, a vendor partner program or a reliable export, and what your plan tier permits. Some vendors restrict access to approved partners, which adds time. We confirm the path during scoping and tell you before quoting if it is limited.
How much does AI automation cost for a healthcare practice?
The cost of AI automation for medical practices depends on how many workflows are in scope, whether your EHR has a usable API, how much clinical judgement the AI has to support, your monthly volume, and the fact that PHI is involved. The AI audit is free and ends with a scoped estimate. Builds are fixed-price, and ongoing support is a flat monthly fee that covers hosting, monitoring and model costs. Our pricing page explains what moves the number.
Can AI automate insurance verification and prior authorization?
AI can do the reading and assembly; a person should still make the call and submit. It can summarize an eligibility response for the scheduled service, check chart notes against a payer's criteria, draft the packet with each criterion linked to its supporting note, and list what is missing. Your staff review the packet, the ordering provider approves clinical language, and submission goes through your usual portal or clearinghouse.
What ROI can a healthcare provider expect from AI automation?
Return depends on how much time your clinicians and staff spend reading and compiling today. In our delivered MindCare Health build, provider prep for an ADHD evaluation went from more than two hours of manual compilation to about five minutes of automated processing, at roughly $0.08 per evaluation, with the provider still reviewing the result. Your numbers will differ, which is why the free audit measures your current process first.
How long does implementation take for a clinic or practice group?
Most builds go live in two to three weeks from a defined scope, and work involving PHI or a restricted EHR can take longer. The MindCare Health pre-assessment system took six weeks with one developer. Practice groups with different templates or policies by location usually start at one site, prove the workflow, then extend it.
Will AI automation replace clinical or administrative staff?
No, and it is not built to. It takes over the compiling and first drafts so clinicians spend their time on judgement and patients, and billing staff spend theirs on the cases that need a person. Every output is reviewed by someone on your team, and every clinical and coverage decision stays with them.
Keep reading
- Healthcare Workflow AutomationIntake, scheduling, referrals and follow-up moving between your EHR, phones and inbox without retyping.
- MindCare Health case studyA delivered build: ADHD pre-assessment briefs that cut provider prep from 2+ hours to about 5 minutes of processing, for 20 to 30 evaluations a week at about $0.08 each.
- Cash-pay physical therapy blueprintAn engagement blueprint, scoped but not built, that includes exercise sheets and superbills generated from therapist notes.
- AI for Healthcare PracticesEverything we build for healthcare teams, in one place.
- AI AgentsHow we build AI agents that take on reading, drafting and review work.
Find the reading your providers should not be doing.
Book a scoping call. We will look at pre-visit prep, prior authorizations and documentation with you, tell you which one is worth handing to AI first, and what it would cost.
Book a scoping call