Hospital platform for AI models in medical imaging
NAIRA is an end-to-end platform for hospitals and clinical services to create, validate, and operate their own Artificial Intelligence models safely.
The Current Paradigm
AI advances fast, but its adoption is limited by structural obstacles
Hospitals face a fragmented ecosystem, with opaque models and without the control or evidence needed to adopt artificial intelligence systematically and safely.
× The Problem
Dataset scarcity
Lack of quality annotated data, especially for complex tasks with inter-center variability.
Collaboration difficulties
Regulatory and logistical barriers to exchanging medical data between hospitals due to privacy concerns.
Lack of traceability
No clear operational evidence: which data, versions, metrics, or limitations were used in the model.
External dependency
Closed solutions that solve a specific task but do not build real internal capacity at the center.
✓ The NAIRA Solution
NAIRA doesn't compete for "the best one-off algorithm". It competes to install a comprehensive hospital capability for controlled, repeatable AI development.
Controlled Workflow
With NAIRA, each center can create private models and maintain them under its control, with metrics, traceability, and governance from day one.
Core Capabilities
What you can do with NAIRA
A complete suite designed specifically for the needs of clinical and medical research environments.
Manage data and annotations with QA
- Dataset organization and version traceability
- Visualization and annotation
- Annotation quality control (QA) and review workflows
- Standardization of labeling protocols
Train and evaluate AI models
- Reproducible training
- Evaluation with clinical metrics
- Comparability across versions and centers
- Generalization and robustness analysis
Generate 'decision-ready' evidence
- NAIRA produces an evidence pack per model:
- Lineage (data/annotations), metrics, limitations
- Clear conditions of use
- Exact version of model and pipeline
Operate models with governance and traceability
- Model Registry with states (candidate, validated, etc.)
- Version control and granular permissions
- Complete audit trail and change records
Collaborate across centers without moving data
- Optional classic federated learning
- Each center trains locally
- Only parameters/model updates are shared, not data
- Total privacy and sovereignty preservation
Strategic Value
Why NAIRA
Security by design and operational advantages that accelerate real AI adoption.
Reduce time and rework
By standardizing and automating critical parts of the workflow, you avoid information silos and optimize hospital resources.
Improve consistency
Ensure total comparability between professionals and different centers through unified metrics and integrated QA.
Build internal capacity
Instead of depending on a single algorithm vendor, you strengthen your hospital's own R&D and deployment capabilities.
Accelerate the path to product
Smooth transition from pilot to product, thanks to building robust evidence and governance from day zero.
Security and privacy by design
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Local/segregated deployment
Infrastructure ready to work with sensitive clinical data on-premise or in a secure cloud.
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Advanced access control
Strict RBAC (Role-Based Access Control) implementation with audit trail and immutable traceability.
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Data federation
Absolute minimization of data movement through optional federated learning.
Want to pilot NAIRA at your center?
If you want to explore a pilot or evaluate NAIRA for internal use (Research mode), contact us to define the use case, data plan, and validation KPIs.