Fragmented data costs. In lives, and in dollars.
Add the predictive layer to the exchange you’ve already built and see the patterns in time to act.
Rural health
Three ER visits. Three different facilities. One rural mother.
150M+
patient records governed
2019
started running production AI in healthcare
30,000+
monthly algorithm requests from users
The analytics layer your vendors promised never arrived.
You know what an HDU should do: predict risk before it becomes a crisis, surface signals while there is still time to act, make your population’s data work for the people it represents.
You have spent a decade building the foundation to get there. ADT, lab, claims, pharmacy, clinical notes all flowing. Your members trust the exchange. Your state has named you in HDU legislation or RHT planning. And your board has approved the path.
But the reporting is still retrospective. The AI promises came with consultants and never came with results.
We've never had this level of access to data across our rural communities. For the first time, we can see what's happening before it becomes a crisis.
Orchestral layers on top. Nothing you’ve built gets replaced.
Most platforms ask you to start over. We don’t.
Orchestral connects to what you’ve already built: HL7, FHIR, ADT feeds, claims, pharmacy, clinical notes. We do not touch your infrastructure. Your existing connections, dashboards, and workflows stay where they are. We add the analytics and AI layer your current platform was never designed to deliver.
Keep what works. Replace what is failing. Add what is missing.
That is the difference between an HIE that adopted the HDU label and one that operates as one.
What an HDU does that your current analytics layer doesn’t.
You have heard the language. Shared data platform. Connect data across systems. Accessible tools and dashboards. Data-informed decision-making. Training and support. New Mexico’s $53M Rural Health Data Hub was scoped around exactly these capabilities.
Orchestral delivers those capabilities and the ones that come next.
| Where you are | Where Orchestral takes you |
|---|---|
| ADT and claims flowing, but no clinical AI in production | Governed AI agents deployed on top of your existing data exchange |
| Retrospective reporting, quarterly at best | Near real-time signal on quality, capacity, and population risk |
| Every new initiative builds its own pipeline | One foundation supports new use cases without rebuilding |
| Reports describe what happened | Models predict what is about to happen, with enough lead time to act |
| Member organizations pay fees and receive exchange | Member organizations pay fees and receive intelligence, monetization paths, and shared AI capability |
Three steps. No rip and replace.
The first question is always the same: what does Orchestral actually touch, and what does my team have to do?
1. Connect
We connect to your existing exchange data. Your current member connections, dashboards, and workflows stay exactly where they are.
2. Configure
We deploy the AI and governance layer on top. You determine which use cases go live first. We scope compliance and data governance requirements before anything is built.
3. Operate
New capabilities are live. Existing workflows are unchanged. Your exchange now operates as a Health Data Utility.
Most HIEs are live within a month depending on your data structure. We scope this in the working session.
What your team gains.
For HIE leadership
Orchestral’s predictive models give HIE leadership the signals your current reporting can’t produce.
Rural hospital stability radar: Predict which facilities are heading toward financial stress before closure becomes inevitable.
Quality early warnings: Surface MCO and regional risk to quality targets while there is still time to intervene.
One foundation, every use case: New initiatives deploy on top of the same data layer. No new pipelines. No new vendor negotiations.
What teams ask first.
How does Orchestral align with the Rural Health Transformation Program?
Do we need to move our data?
Does Orchestral work with our existing data infrastructure?
Can a small Critical Access Hospital participate?
How is Orchestral different from a dashboard or BI tool?
How long from sign-off to first predictions running?
Built by the team behind Rhapsody. Not a data warehouse vendor with a healthcare deck.
Orchestral was built by the team behind Rhapsody, the integration engine purpose-built for health data exchange, running in health systems globally and touching over 200 million patient records. We did not start with a general data platform and adapt it for healthcare. We built for healthcare data from the start.
We are health data infrastructure veterans who got tired of watching states pay for data platforms that never crossed the finish line.
Meets healthcare standards. Not adapted for them.
Orchestral is built on healthcare data standards from the ground up. You are not deploying a general-purpose AI tool and hoping it complies. You are deploying infrastructure designed specifically for the constraints of health data
AI guardrails built into every model deployment. Models operate within defined parameters, with a full audit trail.
Data governance controls included. No shadow pipelines, no ungoverned data movement.
See what Orchestral can do on data like yours. No commitment.
We will show you how Orchestral surfaces care gaps, readmission risk, and program enrollment opportunities on data like yours. Then you decide if it is worth going further.