Data stays in-house
Training and inference run entirely inside your private environment
Private Clinical Decision Model Training
Built on your hospital's private data, trained into dedicated clinical decision intelligence that carries your care delivery into its AI upgrade.
On-premise deployment
Model assets and weights belong to your hospital
Built into critical workflows
Co-created with clinicians and embedded in real care pathways
Our AI upgrade
From Medical Devices to Clinical Intelligence: Our AI Upgrade Journey
For years, myAvro has focused on clinical data capture and intelligent medical hardware, supporting clinical trials around the world. Working closely with hospitals and research teams, we kept seeing the same gap: clinical data volumes keep growing, yet intelligence that genuinely feeds back into care decisions remains scarce.
General-purpose large models cannot reach a hospital’s private data, nor understand the clinical context of a specific department. So we set a clear AI direction: no cloud schemes that let data leave the building. Instead, we bring model training into the hospital’s own environment, so clinical intelligence grows exactly where the data grows.
Phase 1
Medical product foundation
Clinical data capture hardware and trial platforms deployed, building deep domain understanding
Phase 2
AI upgrade begins
A private, security-controlled healthcare AI roadmap is established
Phase 3
Private training system in place
A complete methodology covering data governance, private training and clinical validation
Phase 4
Clinical deployment pilots
Working with clinicians to validate decision-support value in real care workflows
What it is
What is Private Clinical Decision Model Training
Dedicated AI models for clinical decision support, trained on your hospital’s own clinical data inside a private environment. Both the models and the data remain your hospital’s property, with no reliance on uploading data to public large models.
General large models
Data ownership
- Data must be uploaded to the cloud for processing
- Model weights belong to the vendor
- Hospitals struggle to control where data flows
Private clinical models
Data ownership
- Data remains on-premise throughout
- Model assets belong to the hospital
- Data flows are clear and auditable
Fit and compliance
- Training tailored to each department’s context
- Outputs aligned with your own care pathways
- Designed to meet healthcare data security regulations
Capabilities
Four Core Capabilities
Covering the full chain from data to decision.
Clinical data governance
Cleaning, annotation and structuring of multi-source heterogeneous data into high-quality, trainable clinical datasets
Private model training
Task-specific model training and continuous iteration for clinical use cases, so capability grows together with your data
Decision support engine
Clinical assistance such as care-pathway suggestions and risk alerts, provided for physicians to reference in their decisions
On-premise deployment
Delivered and run locally, with compute and models operating inside the hospital’s own environment
How we work
A Five-Step Training Process
A complete path from requirements to production.
1
Discovery
Map clinical scenarios and decision goals
2
Data governance
De-identification, cleaning and expert annotation
3
Model training
Iterative optimisation inside the private environment
4
Clinical validation
Clinician review and feedback-driven refinement
5
Deployment
On-premise delivery with ongoing operations
Security & compliance
Data Security Is Our Baseline
The sensitivity of medical data makes private deployment a prerequisite, not an option.
Data stays in-house
Training, validation and inference all run inside your private environment; raw data never leaves the hospital boundary
De-identification throughout
Data is de-identified and anonymised before entering the training pipeline, reducing privacy exposure
Role-based access control
Data access is scoped by role and department, with every operation logged and traceable
Compliance-aligned by design
Processes are designed to meet healthcare data security regulations and support in-hospital audits
Scenarios
Clinical Use Cases
Finding the right point of intelligence across departments and workflows.
Diagnostic decision support
Combines history and examination data to give physicians differential-diagnosis references
Medication risk alerts
Detects interaction and contraindication risks to support medication safety checks
Medical record QC
Automatically checks record completeness and documentation standards, easing the QC burden
Care pathway guidance
Follows your own pathways and guideline versions to flag the next step in care
Imaging report assistance
Provides structured suggestions for drafting imaging findings and conclusions
Research data insights
Supports retrospective studies and cohort screening on de-identified data
Why myAvro
Why Work With myAvro
Deep healthcare experience
Years of serving clinical data capture scenarios, with a real understanding of hospital workflows
Private and controllable
Data and model assets belong to the hospital, on a transparent and auditable technology path
Co-built with clinicians
Clinical experts take part in annotation, validation and iteration at every stage
Start Your Hospital's Own Clinical Intelligence
Talk to us about how private clinical decision model training can work for you. We will assess feasibility together with your clinical scenarios.