Why start with AI in healthcare now?
The technology is mature, regulations are becoming clearer, and staffing pressure makes smart support essential.
Diagnostic support
AI analyses patient data, recognises patterns in symptoms and suggests differential diagnoses. The physician decides, AI does the groundwork.
Automate administration
From documentation to letters: AI creates draft texts based on the consultation. The physician reviews and approves, typing time is halved.
Patient communication
Chatbots answer frequently asked questions, send reminders and prepare patients for appointments. Available 24/7, always patient.
Knowledge base & protocols
AI searches guidelines, medication interactions and the latest literature. Physicians get well-founded advice without having to dig themselves.
From hype to proven performance
Over the past two years, AI in healthcare has improved explosively. Where MedPaLM 2 scored 86.5% on the MedQA benchmark in 2023, the latest models like GPT-5.1, Gemini 3 and Claude Opus 4.5 achieve scores of 91-94% – well above the average of experienced physicians.
More important than scores: AI is now being used practically. Epic and other EHR vendors are integrating AI assistants, hospitals are experimenting with ambient listening for automatic documentation, and first triage chatbots are running in production.
What does this mean for your organisation?
Less administrative burden: physicians spend less time typing and more time with patients.
Faster access to knowledge: no manual searching through guidelines, AI provides direct answers.
Better patient experience: 24/7 availability via smart chatbots and personalised communication.
Diagnostic support: AI as a second pair of eyes that misses nothing.
How we implement AI in your healthcare organisation.
From initial exploration to working solution: we guide you through the entire process with a pragmatic approach.
Use case inventory.
Where are the biggest opportunities? Together we map out the time drains and bottlenecks. Often administrative tasks, patient communication and knowledge support score highest on impact versus effort.
Proof of Concept.
Within weeks we build a working prototype that demonstrates what AI can mean. With real (anonymised) data and direct feedback from end users.
Privacy & compliance check.
Together with your privacy officer and DPO we ensure the solution complies with GDPR and healthcare regulations. We know the rules and understand how to deploy AI responsibly.
Scalable implementation.
From pilot to production. We integrate with your EHR, train end users and ensure monitoring. Start small, scale up when it works.
Examples of AI in healthcare
AI is already being used successfully for various applications. From triage and documentation to medication monitoring and patient education.
AI-powered triage
Patients describe their complaints via a chatbot that assesses urgency and refers to the right care provider. Primary care and emergency departments already use this to reduce phone pressure.
Practical benefits
Less phone pressure on the practice
Faster referral for urgent complaints
Patient gets an immediate assessment
Automatic documentation
AI listens during the consultation (with consent) and automatically creates a draft report. The physician adjusts where needed and clicks save. Saves up to 50% typing time.
Ambient clinical intelligence
This technology is being rolled out by major EHR vendors like Epic and Oracle Health (Cerner). We can also build similar solutions that connect to your systems.
Medication interaction checker
AI reviews the medication list, flags potential interactions and explains why. Pharmacists and prescribers get well-founded advice without having to search themselves.
On top of existing databases
The AI combines standardised sources with the latest literature for a complete picture.
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AI expertise for healthcare
From concept to implementation.
We combine technical AI knowledge with understanding of the healthcare sector. Our approach: start small, deliver value fast, and scale up what works. Whether you want a chatbot for patient communication or a complex integration with your EHR – we think along and build through.
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Frequently asked questions about AI in healthcare
Privacy, regulations, integration – we understand there are many questions. Here are the most common ones.
What about privacy and GDPR?
Privacy comes first. We exclusively work with AI models that do not use data for training, or we host locally. All solutions comply with GDPR and healthcare regulations. Together with your DPO we determine the right legal basis for processing.
Can AI make mistakes in diagnoses?
Yes, and that's why we position AI as support, not replacement. The physician remains ultimately responsible and makes the decision. AI provides suggestions, sources and a second look – the human decides.
Does this work with our EHR?
Almost always. We build integrations with common EHR systems like Epic, Cerner and others via APIs or HL7/FHIR. In an initial conversation we map out the technical possibilities.
What does an AI implementation cost?
We often start a proof of concept from €10,000 to €25,000. Full implementations vary greatly depending on scope and integrations. We work transparently with fixed prices or time and materials, your preference.
How long before we have something running?
A working prototype is often ready in 4-8 weeks. From there we iterate towards production-ready. Our approach: start small, deliver value fast, expand what works.
Does AI software fall under medical device regulations?
Depending on the application, it may or may not. Software that provides information for diagnostic or therapeutic decisions may qualify as a medical device. We help you determine the right classification and find a Notified Body if needed.
