Hospital-grade AI, built for the providers technology left behind.
PrivateCare AI runs entirely inside your own servers, so patient information never leaves your building. It connects to the systems you already use today. No replacements, no long migrations, no disruption to your staff.
AI THAT RUNS ON YOUR OWN SERVERS. NOTHING LEAVES THE BUILDING.
Built for a market cloud-first vendors simply cannot serve.
Enterprise clinical AI usually needs modern software and a costly overhaul before it can even connect. Most Federally Qualified Health Centers and Critical Access Hospitals don't have that kind of budget, so they've been left out of the AI conversation entirely.
Documentation overload
Physicians in community settings can spend nearly half of their working hours on paperwork instead of patients.
Outdated systems, locked out
Cloud-first AI vendors require modern infrastructure. Institutions running older systems often can't connect at all, unless they can pay for a full replacement.
Shadow AI and HIPAA exposure
Without an approved tool, staff sometimes turn to public AI chatbots to save time on notes, and patient information can leave the building without anyone realizing it.
New rules, no support
Federal rules now require hospitals to automate prior authorization by 2027. Most institutions running older systems have no clear path to get there on their own.
One AI platform, built to run entirely inside your walls.
Every part of PrivateCare AI runs on a server your institution controls, and connects to the systems you already use without replacing anything.
Clinical AI Engine
Trained on medical terminology and clinical coding standards, and built to learn your institution's own documentation style over time.
Legacy System Connectors
Connects directly to the patient records system you already run today. No replacement, no migration, no downtime for your staff.
Ambient Voice AI
Turns the conversation between physician and patient into a structured clinical note automatically, recovering up to two hours a day.
CleanSlate Shadow AI Shield
Notices when staff turn to public AI tools with patient information, and redirects that activity into a secure, fully logged channel instead.
AutoAuth & Revenue Cycle AI
Automates prior authorization and flags documentation gaps in real time, helping recover revenue that would otherwise be lost to denied claims.
MultiLingual Engine
Supports clinical encounters in Spanish, Haitian Creole, Vietnamese, Portuguese, and Arabic, generating compliant English documentation automatically.
GrantReady Analytics
Automates the annual reporting many FQHCs depend on for federal funding, turning weeks of manual work into a few hours.
ClinicalIQ Analytics
Tracks physician workload, forecasts patient demand, and lets your team compare performance against similar institutions. Built for lean administrative teams.
Your patients' data never leaves the building.
Most AI vendors send patient information to an outside cloud for processing. PrivateCare AI does the opposite. For clinics serving undocumented, uninsured, and other vulnerable patients, that difference is often the reason AI becomes possible at all.
Built around your institution, not a one-size-fits-all price tag.
Every institution runs different systems, serves a different population, and works with a different budget. Rather than publishing a fixed price list, we scope every plan around what your institution actually needs.
Tell us about your institution. We'll build a plan around it.
Whether you're a small rural clinic or a regional health network, our team will scope a deployment plan around your provider count, your systems, and your budget, with no obligation.
No published price list. Every plan is scoped to your provider count, your systems, and your budget.
The only platform built to work with the systems you already have.
Enterprise vendors, add-ons tied to a single system, and point solutions all leave a gap somewhere. Here's how PrivateCare AI compares.
| Capability | Enterprise cloud AI (large hospital vendors) |
Legacy system add-ons | PrivateCare AI |
|---|---|---|---|
| Deployment model | Cloud-only, patient data sent externally | Native to one system's own ecosystem only | 100% on-premise or private cloud |
| Works with older systems | Usually requires modern infrastructure first | Locked to a single vendor's platform | Connects to what you already run, no replacement needed |
| Pricing approach | Enterprise pricing, built for large systems | Several vendor contracts stacked together | One plan, scoped to your institution, quote on request |
| Built for FQHC and rural budgets | |||
| Shadow AI detection | |||
| Multilingual clinical documentation | Usually enterprise-only, priced separately | Included, on-premise, five languages | |
| 2027 prior-authorization compliance | Usually needs a separate integration project | Built to meet the requirement automatically |
Impact your CFO and your Chief Medical Officer can both stand behind.
Every module is designed around a documented, measurable outcome, not a vague promise of efficiency.
Laís Costa
Founder & Chief Executive Officer
Software engineer and systems specialist with over 17 years of experience building technology platforms for regulated industries, including healthcare.
A founder who has spent her career solving exactly this kind of problem.
Every major challenge PrivateCare AI takes on is something Laís has already worked through in her career. She has spent 17 years connecting new technology to older systems that were never designed to talk to each other, in industries where mistakes simply aren't an option.
She has also built and deployed AI tools independently, entirely on private infrastructure with no dependence on outside servers, long before founding PrivateCare AI.
She's also the author of an open-source tool that other engineers use to simplify how data moves between systems, with more than 900 downloads by developers around the world.
17+ years in regulated industries
Experience spanning logistics, agricultural technology, and healthcare systems.
Harvard CS50 AI with Python
Also an AWS Certified AI Practitioner and an active member of the ACM.
Tested in production, not just theory
She built and tested this approach in real environments before founding the company.
Compliance isn't a feature. It's the foundation everything else is built on.
HIPAA and HITECH requirements are built into the architecture before a single client contract is signed.
HIPAA and HITECH by design
A full risk analysis, signed agreements with every client, and a clear breach-notification process before go-live.
Encryption and access control
Encryption at rest and in transit, role-based access, and a full audit trail across every module.
Independent security certification
Our team is working toward a formal third-party audit, the standard many state health programs expect from technology vendors.
CleanSlate Shadow AI Shield
Notices unauthorized use of public AI tools on your network and redirects it into a fully auditable, compliant channel.
Bring hospital-grade AI to your institution, without replacing a single system.
Tell us about your systems and how many providers you have. Our team will put together a plan built around your infrastructure within two business days.
- No system migration required
- Starter Plan institutions are typically live within 30 to 45 days; Growth and Enterprise deployments within 60 to 90 days
- A signed agreement in place before we ever access your data