Patient registration and care remain one of the most challenging areas in healthcare facilities: high call volumes, no-shows, and constantly changing schedules overload staff and negatively impact the patient experience. Artificial intelligence solutions enable these processes to be structured, automated, and made predictable.
âIn healthcare, itâs not just speed that matters, but accuracy as well. Mistakes cost far more than in other sectors,â says Aistis Raudys, a developer of artificial intelligence solutions. 
Smart Check-In and Patient Flow Management
AI-powered systems can operate 24/7, check in patients in real time, and select the optimal appointment time based on doctor availability and the nature of the service. By analyzing historical data, they predict no-shows, automatically adjust schedules, and offer available slots to other patients. This helps reduce âempty slots,â make more efficient use of specialistsâ time, and reduce the administrative burden.
More Accurate Diagnostics with AI
In collaboration with Santaros Clinic, we addressed a real-world problem: the slow and often inaccurate analysis of kidney stone composition. Traditional methods were time-consuming and required manual interpretation, which increased the risk of errors. To address this, an AI-based FTIR data analysis model was developed, which automates the interpretation of spectroscopic data. Trained on real-world data, the system can determine the composition of a stone and provide probability estimates within minutes.
âSuch solutions allow doctors to rely on clear data rather than guesswork,â emphasizes A. Raudys.
The result: analysis time reduced by up to 80%, lower probability of errors, and the ability to select treatment more precisely.
AI Call Center in Healthcare
Another problem area is patient service over the phone. Facilities such as the Kaunas Polyclinic handle tens of thousands of calls every month, which places a heavy workload on operators. The AI solution âMedicallâ combines speech recognition (âWhisper,â âWav2Vec2â), call transcription, response generation, and automated appointment scheduling. The system assists operators in real time and generates summaries after each call.
âValue is created when technology helps people work faster, rather than replacing them,â says A. Raudys.
AI Compliance for Regulated Healthcare Institutions
One of the most common barriers in the healthcare sector is that hospitals and clinics cannot use standard AI tools such as ChatGPT or Copilot, as these are incompatible with GDPR Article 9 (governing special-category health data), EU AI Act requirements for high-risk systems, and MDR/IVDR obligations. To address this, AAI Labs developed Merkys.ai, a private AI solution that allows organizations to run AI entirely within their own infrastructure, without cloud services or external APIs.
The system adapts an open-source model (Llama, Mistral, or equivalent) to the organization's own documents (clinical protocols, internal procedures, regulatory files) and provides access via a simple chat interface with role-based access control and a full audit trail. The solution directly aligns with the EU's AI sovereignty priority and is built with the EU AI Act's August 2027 high-risk system requirements for the healthcare sector in mind.
Long-term value for healthcare facilities
These solutions integrate easily with existing systems and can be scaled as patient volumes grow. Over time, artificial intelligence becomes not only a tool for automation but also a key part of a healthcare facilityâs infrastructure, ensuring more efficient, accurate, and reliable service delivery.
FAQ
What are AI solutions in the healthcare industry?
These are artificial intelligence technologies used for diagnostics, patient care, data analysis, and the automation of clinical processes.
How is AI used in medicine?
AI helps analyze medical images (X-rays, MRIs), predict diseases, manage patient flows, and automate administrative processes.
Can AI help diagnose diseases?
Yes. AI can help doctors detect signs of disease at an early stage, but the final diagnosis is always made by a specialist.
How does AI improve patient care?
Chatbots and automated systems allow for faster patient registration, quicker responses to questions, and reduced wait times.
Can AI reduce a clinicâs costs?
Yes. By automating administrative processes and optimizing resources, operational costs can be reduced.
Is it safe to use AI in healthcare?
Yes, provided strict data protection requirements (e.g., GDPR) are followed and certified solutions are used.
How much do AI solutions cost for the healthcare industry?
The cost depends on the complexity of the solution (ranging from simple SaaS tools to complex integrated systems).
What are the most common mistakes when implementing AI in healthcare?
Data quality issues, over-reliance on AI, and insufficient staff training.
Can AI replace doctors?
No. AI is a supportive tool that helps doctors work more accurately and quickly.