HIPAA-ready AI inside your walls for Hospitals and Health Systems
Clinical documentation, prior authorization, coding and care coordination agents on an AI operating system your health system owns: hosted, in your own cloud, or fully air-gapped. On ibl.ai you own all the code and the data, run it model-agnostic across any LLM, and pay with no per-seat pricing — so you can deploy anywhere, from your own cloud to a fully air-gapped network. No need to choose build vs. buy — you get both.
“ibl.ai does amazing work and are great people.”
Everything we do, for health systems
One platform, three ways to run it, and engineers who build inside your environment. Every piece ends up owned by the health system, not rented from a vendor, and PHI stays where you put it.
Where does PHI go when you use AI?
A managed AI vendor can sign a BAA and promise to protect PHI on its own cloud. It cannot hand you the source code, let you choose the model, or keep PHI off its servers. ibl.ai is built so the health system holds all three.
| ibl.ai | A managed AI vendor (ChatGPT Enterprise, Copilot, Claude for Enterprise) | |
|---|---|---|
| Where PHI goes | ibl.aiStays inside your network: your data center, your VPC, or an air-gapped environment next to the EHR | A managed AI vendor (ChatGPT Enterprise, Copilot, Claude for Enterprise)Leaves your network for the vendor's cloud, governed by the vendor's BAA and terms |
| Which models | ibl.aiAny model: Claude, GPT, Gemini, Bedrock, or open weights on your own GPUs so PHI never reaches a model provider. Switch per agent, anytime. | A managed AI vendor (ChatGPT Enterprise, Copilot, Claude for Enterprise)The vendor's own models, on the vendor's roadmap |
| Who owns the code | ibl.aiThe health system: a perpetual Full Code License to the complete platform | A managed AI vendor (ChatGPT Enterprise, Copilot, Claude for Enterprise)The vendor; you rent access to it |
| Pricing shape | ibl.aiA flat license or usage. No per-seat fees, so every clinician, coder and front-desk employee can use it. | A managed AI vendor (ChatGPT Enterprise, Copilot, Claude for Enterprise)Per seat, per month, whether or not the clinician logs in |
| Audit and PHI access logging | ibl.aiEvery PHI access and agent action logged on systems your compliance team controls, with minimum-necessary access by role | A managed AI vendor (ChatGPT Enterprise, Copilot, Claude for Enterprise)The vendor's logs, on the vendor's retention schedule |
| What you keep if you leave | ibl.aiEverything: the code, the data, the agents and their memory, still running beside the EHR | A managed AI vendor (ChatGPT Enterprise, Copilot, Claude for Enterprise)An export, if the contract allows one |
MCP Architecture Guide for Healthcare
How to connect your healthcare systems (EHR, LMS, credentialing, patient portals) to AI agents — with HIPAA compliance.
Read the GuideWhat is an AI-native hospital or health system?
An AI-native hospital or health system is an organization intentionally designed around artificial intelligence as a foundational capability, integrating clinicians and intelligent systems across clinical documentation, care coordination, revenue cycle, research and administration, while keeping patient care the mission. On ibl.ai you own all the code and the data, so protected health information never leaves your own network.
An AI-enabled health system runs a pilot per department — a scribe here, a chatbot there. An AI-native one designs documentation, care coordination and revenue cycle around agents that share one institutional context, from the single practice to the whole network.
The systems of record are the EHR and the interfaces around it: Epic, Cerner or athenahealth, reached through FHIR and HL7, plus the scheduling, practice management and billing systems that carry the claim.
HIPAA is the binding constraint, with Joint Commission accreditation on top for hospitals. A BAA governs a vendor's access to PHI; owning the stack removes the third-party access the BAA exists to govern.
The book's operations, governance, research and infrastructure pillars carry over to a health system; its teaching pillar becomes clinical and continuing medical education. See The AI-Native University.
AI Agents for Healthcare
AI Courses for Healthcare
Practitioner training grounded in primary sources. Each course publishes its full design — module outline, learning outcomes, assessment, and the regulations it cites. Request access to run one with your cohort.
HIPAA-Compliant AI: PHI, BAAs, and Where the Data Lives
What HIPAA actually requires of an AI deployment — the BAA analysis, Security Rule safeguards, minimum necessary, and the architecture that keeps PHI inside your boundary.
Clinical Documentation with AI: Ambient Notes and Review
Deploy ambient documentation safely — accuracy in clinical language, the attestation requirement, note bloat, and measuring whether it returns clinician time.
Medical Coding with AI: ICD-10, CPT, and Denial Prevention
AI-assisted coding that improves accuracy rather than just speed — code suggestion, documentation gap detection, denial prevention, and staying clear of upcoding.
Prior Authorization Automation with AI Agents
Compress the highest-friction administrative process in healthcare — payer requirement lookup, packet assembly, status tracking, and appeal drafting.
Patient Education Agents: Health Literacy and Safety
Patient-facing AI that explains conditions and discharge instructions safely — reading level, language access, scope boundaries, and symptom escalation.
AI in Clinical Decision Support: Evidence, Limits, and Liability
Deploy clinical decision support responsibly — evidence grounding, automation bias, transparency obligations, and where liability actually lands.
How ibl.ai compares
The Agentic AI Operating System for Healthcare
ibl.ai gives hospitals, health systems, clinics and payers their own Agentic AI Operating System: the platform behind Agentic OS, Agentic Vibe and Agentic LMS, deployed where you decide and owned outright.
PHI never leaves the environment you control. Any model answers, including open-weight models on your own GPUs, and no AI vendor's pricing or roadmap decides your clinical tooling.
Which healthcare systems do the agents connect to?
Epic, Oracle Health (Cerner) and MEDITECH, exposed to agents through HL7 FHIR and MCP servers the health system owns.
Agents answer from the chart and the approved protocol, with the citation, under minimum-necessary access.
What do healthcare AI agents actually do?
Note drafting, chart summaries and protocol lookup for clinician review, grounded in your approved resources.
Agents assist documentation; they do not diagnose, and the clinician makes every clinical decision.
How does a health system keep control of PHI and models?
How can a health system run ibl.ai?
What services come with the platform?
What does it cost, and who owns it?
How do we start?
What our partners say about us
Chris Gabriel | Google
Lorena Barba | George Washington University
Dr. Juana Mendenhall | Morehouse College
Juile Diop | MIT
Adam Tetelman | Nvidia
Jason Dom | American Public University System
Benjamin Breyer | Columbia University
Ken Fujiuchi | SUNY
Erika Digirolamo | Monroe College
David Flaten | SUNY
David Vise | Modern States Education Alliance
Linda Wood | ARM Institute (U.S. Department of Defense)
Chris Gabriel | Google
Lorena Barba | George Washington University
Dr. Juana Mendenhall | Morehouse College
Juile Diop | MIT
Adam Tetelman | Nvidia
Jason Dom | American Public University System
Benjamin Breyer | Columbia University
Ken Fujiuchi | SUNY
Erika Digirolamo | Monroe College
David Flaten | SUNY
David Vise | Modern States Education Alliance
Linda Wood | ARM Institute (U.S. Department of Defense)
Frequently Asked Questions
An AI-native hospital or practice is designed around AI as a foundational capability across clinical documentation, care coordination, coding, revenue cycle and research — one institutional context, not a pilot per department.
Ownership is the test: on ibl.ai you own all the code and the data, so PHI and the audit trail HIPAA and Joint Commission review depend on stay inside your own network.
It is a complete AI infrastructure that lets healthcare organizations deploy, customize, and control AI agents across every function — clinical support, patient education, medical coding, compliance, and operations.
Unlike closed SaaS tools, you own the entire codebase and deploy on your own servers. PHI never leaves your infrastructure.
Yes. ibl.ai deploys entirely on your infrastructure — air-gapped if needed. All PHI stays within your environment, every agent interaction is logged and auditable, and you control all access policies.
You own the full source code. No third-party vendor ever processes or stores your patient data.
ibl.ai integrates with EHR platforms like Epic, Cerner/Oracle Health, Allscripts, athenahealth, and Meditech. It connects to practice management, lab information, and radiology systems via HL7 FHIR and standard healthcare APIs.
SSO is supported via Okta, Azure AD, SAML, and smart card authentication.
DAX and Abridge are cloud-based SaaS tools — your clinical data flows through their servers. ibl.ai runs entirely on your infrastructure with full code ownership.
You control the AI models, the data, and the deployment. No vendor lock-in, no per-clinician pricing, and no third-party access to PHI.
Yes. ibl.ai is LLM-agnostic and supports models from OpenAI, Google, Anthropic, and others. You can run models locally on your own GPUs for maximum PHI protection, or use cloud APIs where compliance allows.
Clinical support agents provide evidence-based guidance, drug interaction checks, and protocol recommendations — grounded in your organization's approved clinical resources.
Medical coding agents assist with ICD-10 and CPT code selection, claim optimization, and denial prevention — all within your own infrastructure.
Yes. A clinical documentation agent (AI medical scribe) drafts structured notes and after-visit summaries from the encounter and writes them back to your EHR, improving CDI — without sending audio or notes to a vendor cloud.
A prior authorization agent checks payer rules, assembles requests with supporting evidence, tracks status, and drafts appeals. Both run air-gapped, so PHI never leaves your servers.
A typical pilot deploys agents in one department within a few weeks to demonstrate clinical value and HIPAA compliance. Organization-wide deployment scales from there.
We start with a free 30-minute assessment to identify the highest-impact use cases for your organization.
Bring us a hard problem. Keep the code.
Run Healthcare AI on your own terms
Start free on our cloud today, or take the whole codebase into your own infrastructure. Either way our engineers work alongside your team, and you own all the code and the data.
ibl.ai is family-owned and operated from New York, NY — a U.S.-headquartered, domestically-owned long-term partner, not a vendor that sells licenses and moves on. · SOC 2 Type II certified
Private AI you own — for healthcare
Run a self-hosted, private LLM platform on your own servers — on-premise or air-gapped. You own the code, data, and models, with no per-seat fees.