Platform
A clinical intelligence layer for chronic disease care
Healthcare organisations already generate large amounts of clinical information. The challenge is converting that information into prioritised and coordinated action.
Cardiomnis AI is being developed as an intelligence layer that can work with approved healthcare data sources, identify important patterns and support structured care workflows.
Platform modules
Five connected areas of intelligence
Each module is being designed to address a distinct part of the detection-to-prevention pathway while sharing a common longitudinal view of the patient.
Patient intelligence
Develop a longitudinal view of clinical risk, laboratory trends, medications, comorbidities and previous care activity.
Care-gap intelligence
Detect missing tests, delayed reviews, unresolved referrals and incomplete follow-up processes.
Clinical workflow support
Present prioritised information within workflows used by healthcare professionals and care-coordination teams.
Population intelligence
Help organisations understand risk, screening completion and care-process performance across patient populations.
Research intelligence
Support approved cohort identification, feasibility analysis, registries, retrospective studies and real-world evidence initiatives.
Conceptual platform workflow
From approved data to measurable action
- 1Approved data sources
- 2Longitudinal patient context
- 3Clinical intelligence
- 4Prioritised worklists
- 5Coordinated action
- 6Measurement
This diagram illustrates the intended concept of the platform. It does not represent a deployed technical architecture.
Data foundations
Potential data sources
Depending on the deployment and applicable approvals, the platform is being designed to work with information from sources such as:
- Electronic health records
- Laboratory information systems
- Medication and prescription records
- Claims and utilisation data
- Health assessments
- Clinical registries
- Remote monitoring systems
- Patient-reported information
Cardiomnis AI does not require or accept patient data through the public website.
Responsible development
Developed responsibly from the start
The platform is being developed as clinical decision-support and workflow technology for qualified healthcare professionals and authorised organisations—not as autonomous medical practice.
Our development approach prioritises explainable information, validation in relevant healthcare settings before broader deployment, privacy-conscious data handling and continuous performance monitoring. Clinical decisions always remain with appropriately qualified professionals.
Interested in shaping the platform with us?
We are exploring design partnerships, research collaborations and pilot opportunities with healthcare organisations.