Managed patient-facing agents billed per agent, or clinical AI running inside the health system's own network
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.
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Hippocratic AI built patient-facing agents around a safety-first premise, with clinically supervised design and voice workflows for outreach, follow-up, and care navigation. For a health system that wants those agents running next quarter, that focus is a genuine advantage.
It is delivered as a managed service, so protected health information is processed on the vendor's infrastructure under a business associate agreement, and pricing is tied to agent usage rather than to a platform license.
A health-system-owned platform removes the disclosure rather than governing it. Models run inside the clinical network, so PHI never leaves systems the organization already secures and audits for the EHR.
This page compares the two on what actually gates clinical AI: where PHI goes, how the agents integrate with Epic or Oracle Health, and who controls the model when clinical behavior has to change.
by ibl.ai
Owned agentic AI platformby Hippocratic AI
Managed healthcare agent service| Criteria | Self-Hosted AI | Hippocratic AI |
|---|---|---|
| Out-of-the-Box Readiness | Production agents for patient outreach, care navigation, clinical documentation, prior authorization, and staff training once deployed, configured to how your organization actually works. | Immediately useful — clinically supervised patient-facing agents with voice workflows purpose-built for outreach and care navigation. |
| Integration With Your Systems | Deep integration with Epic, Oracle Health, athenahealth, and your patient-communication stack over APIs and MCP, running inside your own network. | Connects to common systems, bounded by the connectors the vendor has built. |
| Extensibility | Build and own workflows the vendor has not thought of, because you hold the code. | Configurable within the product; capabilities outside it require the vendor to build them. |
| Any-LLM & Model Control | Run any open or commercial model, route by cost, latency, and capability, and switch anytime. | Runs on its own healthcare-tuned model stack. |
| Criteria | Self-Hosted AI | Hippocratic AI |
|---|---|---|
| Self-Hosting / On-Prem / Air-Gapped | Runs on your servers, your private cloud, or fully air-gapped with zero external calls. | Runs in Hippocratic AI's cloud; it cannot be self-hosted or air-gapped. |
| Where the Data Lives | protected health information (PHI) never leaves your environment, and every interaction is logged for audit. | Processed and retained on the vendor's infrastructure under your agreement. |
| Source Code Ownership | You hold the full source and can audit, fork, and extend every layer. | You rent access; the platform and its roadmap belong to the vendor. |
| Fit With HIPAA, the HITECH Act, and BAA requirements | Data stays inside your perimeter, which is the simplest posture to evidence under HIPAA, the HITECH Act, and BAA requirements. | Vendor compliance coverage under shared-responsibility terms. |
| Criteria | Self-Hosted AI | Hippocratic AI |
|---|---|---|
| Cost at Scale | Flat license plus compute you own — extending access across hospitals and health systems does not multiply the bill. | usage-based pricing tied to agent activity, so cost grows with the size of the organization rather than the work done. |
| Time-to-Value | Requires deployment and integration, or a partner who does both for you. | Usable almost immediately with no infrastructure work. |
| Support & Maintenance | Self-managed, or fully supported with forward-deployed engineers. | Fully managed by Hippocratic AI. |
| What You Keep If the Relationship Ends | A working platform and all your data, still running on your own infrastructure. | Whatever the contract allows you to export. |
Self-hosting means PHI is processed inside the clinical network, so there is no business associate to oversee and no subprocessor chain to track.
A BAA is a real and standard control that allocates duty and liability, and it is how most healthcare technology is bought.
A BAA makes cloud clinical AI defensible. It does not make it private. Which one a system needs depends on the workload and the board's risk posture.
An owned platform serves patient outreach and also clinical documentation, coding support, prior authorization, and staff training from one deployment and one EHR integration.
Hippocratic's focus on patient-facing agents is why they are good, and a focused product needs no platform strategy to deliver value.
Systems buying one capability are well served by a specialist. Systems planning AI across clinical and administrative work need a platform underneath it.
When the health system owns the platform, it sets escalation thresholds, scripting, and guardrails, and changes them immediately after a safety review.
In a managed service, clinical behavior changes on the vendor's release schedule and within the bounds their product allows.
After an adverse event, the ability to change agent behavior the same day is worth more than any feature on the roadmap.
Self-hosting eliminates the disclosure entirely rather than governing it through a business associate agreement.
Purpose-built, clinically supervised outreach agents deliver a narrow capability fast, without an infrastructure program.
Documentation, coding, prior authorization, and staff training should share one platform and one EHR integration rather than accumulating separate vendors.
Escalation thresholds and scripting should follow the system's clinical governance and change on its timeline, not a vendor's release cycle.
Timeline: Four to ten weeks depending on integration count and review requirements
Timeline: Days to a few weeks
ibl.ai is the agentic AI platform where you own all the code and the data. You self-host the entire stack inside your own perimeter, run it model-agnostic across any LLM and switch anytime, and pay by usage with no per-seat pricing — so you can deploy anywhere: your cloud, on-premise, GovCloud, or fully air-gapped.
ibl.ai runs inside the clinical network, so protected health information is processed by systems the health system already secures and audits for the EHR — no business associate for the platform, and no subprocessor chain to track. Agentic OS integrates with Epic, Oracle Health, and athenahealth over internal endpoints, applies guardrails and PII redaction before any model sees a record, and logs every interaction for compliance review. Clinical escalation thresholds and scripting are the system's to configure and change immediately after a safety review. You own all the code and the data, run any model, and can deploy on any cloud, on-premise, or air-gapped, on a flat license rather than per agent or per seat.
Full source code under a perpetual license, running on your infrastructure. Not API access to someone else's platform — the stack itself is yours.
Run any LLM — Claude, GPT, Gemini, Llama, Command, or your own fine-tune — and switch providers without rewriting the platform.
Usage-based billing against a budget cap you set. Cost tracks what your organization actually uses, not how many people you employ.
Your cloud, your VPC, on-premise, GovCloud, or a fully air-gapped network with no outbound connectivity.
1.6M+ users across 400+ organizations run the platform this way, including NVIDIA, MIT, and Syracuse University.
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.
See how ibl.ai deploys AI agents you own and control—on your infrastructure, integrated with your systems.