AI-Driven Healthcare

Unlock the potential of data and Artificial Intelligence in healthcare

Data and AI in Healthcare

Comprehensive support for the Healthcare sector

We support the healthcare sector across the entire scope of data transformation – from acquiring and integrating information, through process automation, to the implementation of Artificial Intelligence–based solutions that drive organizational growth.

By collaborating with medical institutions and healthcare companies, we help them effectively harness the potential of Artificial Intelligence. Our goal is to make their everyday work easier, increase efficiency and security, and create solutions that support both doctors and patients. In this way, we become a trusted partner in building modern and reliable healthcare.

Lekarka w białym fartuchu i ze stetoskopem na szyi siedzi przy biurku, pracując na laptopie. Na biurku znajduje się także tablet i lampa biurkowa, a w tle widać okno.

Our implementations enable companies in the healthcare sector to increase operational efficiency, simplify work, and ensure data security.

How do we work with data, processes, and AI?

Data Management

We provide strategic consulting, design, and implement data architectures (on-premises, cloud, hybrid).

Advanced AI techniques and implementation

Explainable Artificial Intelligence (XAI – Explainable AI), recommendation systems, MLOps – implementation, monitoring, ethics, and responsibility in AI.

Machine Learning and Deep Learning

Machine Learning & Deep Learning – supervised and unsupervised learning, classification, prediction, segmentation and clustering, machine algorithms, neural networks and their architectures, mathematical and probabilistic modeling.

Data Exploration and Preparation

Data processing, data cleaning, feature engineering, dimensionality reduction, multivariate analysis.

Statistics and Data Analysis

Descriptive statistics, statistical inference, time series analysis, extrapolation and interpolation.

Custom Software

We create dedicated solutions that support the automation and digitisation of internal and external processes. From business analysis to implementation.

Modern healthcare powered by AI

AI supports medical companies both in patient care
and process optimization

Fully leveraging the potential of data and implementing Artificial Intelligence–based solutions in the medical sector is not just a matter of innovation – it is a strategic step towards more effective patient treatment, personalized care, and the optimization of clinical and organizational processes.

Artificial Intelligence, based on well-prepared data, supports doctors and medical institutions in making more accurate diagnostic and therapeutic decisions, enables the customization of services to individual patient needs, and automates processes, thereby reducing the risk of errors and accelerating treatment outcomes.

From clinical data analysis, through advanced therapeutic recommendations, to intelligent management tools – AI is becoming a key element of modern medicine. Artificial Intelligence increases efficiency and enhances the quality of healthcare delivery.

Lekarka w białym fartuchu i ze stetoskopem na szyi siedzi przy biurku, pisząc na kartce obok otwartego laptopa. Na biurku stoi lampa, a w tle widać okno.

They have trusted us

Healthcare

Healthcare

Healthcare

Healthcare

Healthcare

Healthcare

Healthcare

Healthcare

Implementing AI in Healthcare

A thoughtful approach is the key to success

Implementing Artificial Intelligence in healthcare requires not only modern technologies, but above all a thoughtful approach aligned with the strategic goals of the organization.

The success of AI depends on skillful management, proper integration, and addressing challenges related to data quality and availability. Only then does Artificial Intelligence become real support in building competitive advantage, improving operational efficiency, and enhancing the quality of patient care.

Institutions that invest in AI are not only adopting modern solutions but also investing in the future of healthcare – making it more effective, safer, and better tailored to patient needs.

Starszy lekarz z siwymi włosami i okularami, ubrany w biały fartuch i ze stetoskopem na szyi, siedzi przy biurku i pisze na kartce obok laptopa. Na biurku stoją także filiżanka kawy i lampa, a w tle widać okno.

How to properly approach AI implementation?

Solving the data problem

Why?

Application integration remains a major challenge and is likely one of the factors contributing to the fact that only 51% of projects in healthcare organizations move from the pilot phase to production.
Behind the biggest implementation barriers (such as integration and security) lie issues related to the volume, complexity, and quality of data.

How?

Invest in data technologies that add data structure and service layers in order to eliminate issues of volume, complexity, and accessibility.
Modernize management to introduce adaptive data management, which incorporates processes supporting identification, development, and delivery of more advanced analyses using Artificial Intelligence.

Better use of AI management

Why?

Healthcare delivery organizations (HDOs) use Artificial Intelligence to differentiate themselves and improve operational efficiency, market share, and revenues.
Healthcare providers prefer AI to be explainable, which is why it enjoys strong interest and trust, while skepticism is in the minority.
Attempts are being made to measure the success of AI initiatives, but to be truly meaningful, they must be aligned with the organization’s strategic goals.

How?

Establish rules for investing in and managing Artificial Intelligence across the entire organization.
Identify AI opportunities that are strategically aligned and both technically and organizationally feasible for implementation.
Oversee implementations by focusing on managing organizational and cultural change.

Artificial Intelligence designed for healthcare

3 must-have AI solutions for the Healthcare industry

Medical Assistant

For doctors: extracts information, summarizes medical documentation, and identifies key patient data, making it easier for doctors to make decisions.

For patients: personalized communication tailored to patient needs. Receiving informational materials adapted to individual requirements.

Speech-to-text

For doctors: conversation analysis, extraction of key information, preparation of summaries in a structured format, highlighting keywords.

For customer service: supporting consultants by suggesting current offers, available appointments, and patient emotions and responses. Automatic conversation summaries, evaluation, and suggested conclusions.

Process Automation

For administrative staff: streamlining appointment scheduling, patient registration, and documentation processes. AI agents intelligently adapt workflows, reduce administrative burdens, and ensure smoother operations.

For patients: automated scheduling systems powered by AI agents improve registration processes, deliver personalized visit reminders, and enhance communication, ensuring more tailored and timely care.

“We appreciate both the technological expertise and understanding of the specifics of medical data that the 3Soft team has brought to the table. The collaboration was professional, and the system remains under constant maintenance and development, which gives us a complete sense of security and readiness for the next stages of transformation and AI in our environment.”

Łukasz Kołkowski

Group CIO at American Heart of Poland & Scanmed

Lekarz wskazuje na zdjęcia rezonansu magnetycznego mózgu i kręgosłupa wyświetlone na podświetlonej tablicy wraz z innymi wynikami obrazowania medycznego.

The future powered by Artificial Intelligence

AI as a pillar of transformation
in the medical sector

59%

of companies in the medical sector plan significant investments in Generative AI over the next 2 years – that’s up to 90% more than today*.

However, it is crucial that these investments are directed towards areas that deliver real business value to institutions. At 3Soft, this is exactly what we focus on.

* Source: NTT Data Global GenAI Report, 2025

Młody lekarz w białym fartuchu i ze stetoskopem na szyi patrzy na tablet, stojąc przy ścianie o betonowej fakturze

How does AI support companies in the Healthcare sector?

01: Process optimization
Automation of administrative and clinical tasks streamlines the operation of healthcare facilities. It reduces the risk of errors and shortens patient service time.
02: Better diagnostics and medical decisions
AI analyzes vast sets of clinical data, supporting doctors in making faster and more accurate diagnoses and therapy selections. As a result, decisions are more precise and evidence-based.
03: Personalized care
AI-powered technologies enable treatments and services to be tailored to the individual needs of each patient. This increases the effectiveness of therapies and improves the overall healthcare experience.
04: Support for doctors and staff
AI relieves employees of routine tasks, such as documentation or scheduling. This allows them to focus on what matters most – direct patient care.
05: Data security and control
AI-based implementations, especially in on-premises models, ensure full control over medical data. This minimizes the risk of breaches and increases patient trust.

Compare the possibilities and choose the right direction

The key to success is choosing the right infrastructure for the use case

	Hybrid model	Cloud	On-premises
Treatment and diagnostics	Combining symptom analysis in the cloud with local sensitive patient data Analysis of medical imaging to support diagnosis and clinical decision-making	No recommendation to implement treatment and diagnostics use cases solely within a cloud environment	Early detection of complications through health monitoring systems Supporting diagnosis and personalized treatment planning Therapy personalization through genetic data analysis
Patient communication and support	Supporting symptom checks, triage, and guidance via chatbots	Personalized communication and educational materials tailored to patients Patient feedback analysis to improve service quality and meet needs	No recommendation
Process automation	Automating appointment scheduling and reminders via chatbot	Automating administrative tasks, allowing staff to focus on patient care	Automating medical documentation based on patient interactions
Data and model optimization	Local IoT data processing with cloud-based analysis for real-time health monitoring	No recommendation	Generating synthetic data for safe and effective model training