AI development, end to end
From framing the problem and preparing the data through to a trained model running in your infrastructure. We take projects from an idea on a whiteboard to something in daily use.
↘AIRGO / AI ENGINEERING
AI-powered applications. AI-engineered solutions.
Task-specific. Explainable. Deployable.
AIRGO designs and builds AI systems for businesses, the public sector and research teams. Scientifically grounded, explainable, and wrapped in an interface the people who actually use it can understand.
What we offer for HealthcareAIRGOEngineered for the journey.
Machine learningExplainable AIData platformsModel validationVisual analyticsOn premises deployment
Machine learningExplainable AIData platformsModel validationVisual analyticsOn premises deployment
01 / What we do
What we do
We do not just provide AI. We ground our AI models to your needs and your data and we deliver scientific-based AI-powered platforms, tools, solutions.
Explainability & validation
Explainability, robustness testing and documented validation for models that carry real consequences. This lets you show why a system behaves as it does, not only that it scores well.
↘Platforms & tools
Data collection with quality control, registries, dashboards, device management and review interfaces. We also provide focused technical reviews of existing models, proposals and roadmaps.
↘02 / Where we fit
We fit in every phase of your project
Some clients come to us with a folder of spreadsheets and no idea what is in it. Others come with a trained model and a deadline to prove it works. Both are fine. We can take a project from the first messy export to a system in daily use. We can also step in at the exact stage where your team needs help and hand the project back cleanly when it is moving again.
You do not need “an AI model.”You need a working solution.
Your data is fragmented
We collect, clean, harmonise and structure data from spreadsheets, instruments, devices and existing systems. This creates a dependable foundation for analysis and AI.
Your model is not ready for real world use
We test performance, calibration, uncertainty and robustness. We add explainability, identify evidence gaps and turn the model into a usable documented workflow.
Your team spends too much time extracting answers
We build visual analytics, automated quality controls, alerts and grounded AI assistants. These tools help people understand data and act sooner.
03 / In practice
Our Products
Showing 8 products
Patient registry & examination timeline
A private web application where a department records examinations, imaging and outcomes against a single patient timeline. Usable both as a study registry and as daily record keeping. Built in quality control flags missing or inconsistent entries at the moment of entry, not six months later when the analysis fails.
Legacy data rescue
Years of unstructured records from any public or private sector department including free text, scanned forms, folder trees, dead databases. All converted into a modern, structured database that respects privacy. Most departments are sitting on a valuable dataset they can't currently query. This is the step that makes everything after it possible.
AI in routine care, prospectively
Taking an AI model out of the retrospective study and into the daily workflow is not as naïve as it seems. We provided it for a client, integrated it into the existing system, running on their infrastructure, with case level explanations shown alongside every result and monitoring in place from day one.
AI assisted calibration suite for air quality sensors
Turns raw low cost sensor output into data that is comparable with reference measurements. It ingests sensor and colocated reference measurements, applies machine learning correction on top of the manufacturer algorithms, and reports how much the correction actually improved agreement making calibration a documented step instead of an informal one.
Device management platform
The administrative backbone of a distributed network: register devices, track configuration, location and health, and spot units that have gone silent or started misbehaving. The layer that makes running dozens of instruments practical.
XAI suite & evidence based validation workbench
A workbench for building, explaining and validating AI models before anyone trusts them. It couples model development with explainability outputs and an assessment layer covering performance, calibration, uncertainty and reporting quality. Across domains, the same validation logic serves medical imaging, air quality, industrial and materials applications.
LLM assisted data analytics platform
Ask questions of your measurement data in plain language and get answers you can trace back to the source. Works across sensors, instruments and operational records. It supports knowledge extraction, summarisation and reporting on top of data you already have.
Forecast & anomaly watch
Demand, consumption, load, cost, failures. A model trained on your own history that produces a forecast you can plan against and an alert when today doesn't look like it should. Small, specific, and measured against what you'd have done without it.
AIRGO / RESPONSIBLE PRACTICE
Trust, Security
& Standards.
AIRGO maintains documented management systems and compliance programmes for responsible AI development, information security, service quality and data protection.
MANAGEMENT SYSTEMS & COMPLIANCE PROGRAMMES
ASSESSMENT BASIS
These conformity statements are based on assessments conducted by AIRGO, not an independent certification body. AIRGO maintains supporting evidence and takes responsibility for the statements. Each statement identifies the covered activities, applicable standard and amendments, assessment date and any permitted exclusions.
Responsible AI — ISO/IEC 42001:2023
Our AI management system conforms to ISO/IEC 42001:2023 within its stated scope, supporting documented governance, risk management and oversight throughout the AI lifecycle.
Select a standard in the moving carousel to read its full statement.
04 / Full journey
We fit in every phase of your project.
Project stages move automatically. Pause or browse at your own pace.
What you have now
Spreadsheets, exports, scanned forms, legacy databases, sensor logs.
Tool: Data auditConsolidation & structuring
One schema instead of forty files.
Tool: Bidirectional Excel ↔ database syncQuality control
Missing values, duplicates, impossible entries, drift between sites.
Tool: Automated QC rules + review screenCuration & annotation
Labels, ground truth, expert review.
Tool: Annotation and adjudication interfaceBaselines & classical ML
The honest first answer.
Tool: Experiment trackingDeep learning
When the data justifies it.
Tool: Training pipelinesExplainability
Case level, not just global.
Tool: XAI suiteValidation & evidence
Calibration, uncertainty, robustness, reporting quality.
Tool: Evidence based assessment layerLLM layer
Knowledge extraction, grounded in your own documents and literature.
Tool: Retrieval + groundingInterfaces & visualization
What the clinician, operator or manager actually opens.
Tool: Dashboards, registries, viewersDeployment
On your infrastructure, on your terms.
Tool: Packaging, on premises installMonitoring & handover
Drift, retraining, documentation, training your team.
Tool: Monitoring dashboard05 / AIRGO
Research discipline. Production delivery.
AIRGO started from a conviction: not general AI, but AI engineered specifically for the task at hand. Our doctoral work and publications sit in explainable AI and medical imaging. This is where we learned that a model nobody can interrogate is a model nobody will use.
The other thing we learned is that the model is rarely the hard part. End users don't care about architectures, and often have no background in AI or data at all. They need something that opens fast, shows them what they need, tells them when to be suspicious of it, and fits the way they already work. That is why our team includes visualization specialists and tool makers, not only AI scientists. It is also why almost everything we deliver comes with an interface, not just weights.
That habit carries into every project, medical or not: understand the data before the architecture, measure honestly, write down why.
50Scientific publications
20Conference proceedings
15Research projects
03Partner countries: Greece, Germany, Cyprus
From possibility to practice
Good science.
Useful AI.
Bring us the problem you want to solve. Together, we can turn your data and ideas into something your team can use every day.
Let’s build something useful