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.
Neural networks when the task and data justify them.
Conceptual illustration · not live measurementsWe 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.
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.
Explore the full journey →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.
Explore the full journey →Data collection with quality control, registries, dashboards, device management and review interfaces. We also provide focused technical reviews of existing models, proposals and roadmaps.
Explore the full journey →Find an idea that fits. Choose a product below, browse three at a time, or open any card for the full story.
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AIRGO / Research background
Before AIRGO, our Lead AI Engineer, Dr. Ioannis D. Apostolopoulos, spent four years as a researcher with universities, research institutes and university hospitals in Greece and Germany. In those labs, clinics and computing centres, AI had to work on real data and hold up under expert review. Most of the methods behind AIRGO were developed and tested there.
FORTH / ICE-HTFoundation for Research and Technology – Hellas · Patras, Greece
Applied machine learning for environmental sensing and air-quality modelling.
LAQSFORTH/ICE-HT · Patras, Greece
Low-cost sensor networks, sensor calibration and PM2.5 forecasting.
SAMPFORTH/ICE-HT · Patras, Greece
Data-driven methods that work alongside physics-based simulation.
IDEAS · University of PatrasDepartment of Mechanical Engineering & Aeronautics, University of Patras · Greece
Machine learning for engineering design and monitoring problems.
ACTA · University of ThessalyDepartment of Energy Systems, University of Thessaly · Larissa, Greece
Artificial intelligence and computational methods for technical and energy systems.
G. Gennimatas HospitalGeneral Hospital of Athens "G. Gennimatas" · Athens, Greece
AI-assisted ophthalmic screening from retinal imaging.
University Hospital of PatrasUniversity General Hospital of Patras · Greece
Explainable deep learning for nuclear medicine imaging.
TU DresdenDresden, Germany
Research on AI for clinical decision support.
University Hospital DresdenUniversity Hospital Carl Gustav Carus Dresden · Germany
Machine learning for endocrine and metabolic diagnostics.
ZIH · TU DresdenTUD Dresden University of Technology · Germany
Scalable AI workflows on high-performance computing infrastructure.
Dr. Apostolopoulos took part in these collaborations as an individual researcher. Institution names are given to describe his research background and do not mean that any institution endorses AIRGO or its services.
Select an institution to read about the research.
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.
AIRGO on LinkedIn ↗AIRGO maintains documented management systems and compliance programmes for responsible AI development, information security, service quality and data protection.
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.
AI governance & oversightOur information-security management system conforms to ISO/IEC 27001:2022 within its stated scope, with documented controls for protecting information and managing security risks.
Information risk & controlsOur quality management system conforms to ISO 9001:2026 within its stated scope, supporting consistent project delivery, customer requirements and continual improvement.
Project delivery & improvementWe process personal data in accordance with the GDPR obligations applicable to our activities and responsibilities, supported by documented processing arrangements, privacy safeguards and procedures for individuals’ rights.
Privacy safeguardsOur open-source licence compliance programme conforms to ISO/IEC 5230:2020, and our open-source security assurance programme conforms to ISO/IEC 18974:2023, within their stated scopes.
Licence compliance programmeOur open-source licence compliance programme conforms to ISO/IEC 5230:2020, and our open-source security assurance programme conforms to ISO/IEC 18974:2023, within their stated scopes.
Open-source security assuranceThese 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.
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.
We collect, clean, harmonise and structure data from spreadsheets, instruments, devices and existing systems. This creates a dependable foundation for analysis and AI.
We test performance, calibration, uncertainty and robustness. We add explainability, identify evidence gaps and turn the model into a usable documented workflow.
We build visual analytics, automated quality controls, alerts and grounded AI assistants. These tools help people understand data and act sooner.
Spreadsheets, exports, scanned forms, legacy databases, sensor logs.
One schema instead of forty files.
Missing values, duplicates, impossible entries, drift between sites.
Labels, ground truth, expert review.
The honest first answer.
When the data justifies it.
Case level, not just global.
Calibration, uncertainty, robustness, reporting quality.
Knowledge extraction, grounded in your own documents and literature.
What the clinician, operator or manager actually opens.
On your infrastructure, on your terms.
Drift, retraining, documentation, training your team.
We collect, clean, harmonise and structure data from spreadsheets, instruments, devices and existing systems. This creates a dependable foundation for analysis and AI.
We test performance, calibration, uncertainty and robustness. We add explainability, identify evidence gaps and turn the model into a usable documented workflow.
We build visual analytics, automated quality controls, alerts and grounded AI assistants. These tools help people understand data and act sooner.
Spreadsheets, exports, scanned forms, legacy databases, sensor logs.
Tool: Data auditOne schema instead of forty files.
Tool: Bidirectional Excel ↔ database syncMissing values, duplicates, impossible entries, drift between sites.
Tool: Automated QC rules + review screenLabels, ground truth, expert review.
Tool: Annotation and adjudication interfaceThe honest first answer.
Tool: Experiment trackingWhen the data justifies it.
Tool: Training pipelinesCase level, not just global.
Tool: XAI suiteCalibration, uncertainty, robustness, reporting quality.
Tool: Evidence based assessment layerKnowledge extraction, grounded in your own documents and literature.
Tool: Retrieval + groundingWhat the clinician, operator or manager actually opens.
Tool: Dashboards, registries, viewersOn your infrastructure, on your terms.
Tool: Packaging, on premises installDrift, retraining, documentation, training your team.
Tool: Monitoring dashboardBring 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 ↗Tick what your project needs. Watch our answer change.
