We build AI-fueled web & mobile apps for the US and Europe medical sectors

We create scalable & reliable AI solutions for new and established businesses. Gain a competitive edge with next-level AI software.

Scroll to see more

Our AI product development services

Audio recognition, opinion mining, or credit scoring – it’s just the tip of the AI iceberg. Here’s what you can do with our help.

Computer Vision

Create convenient & accessible apps that can identify objects, read documents or recognize faces.

Natural Language Processing

Emotion recognition, speech translation, or text summarization - all this and more with our NLP solutions.

Natural Language Generation

Think outside the bot! Build a virtual assistant that will respond to your users' questions & boost customer satisfaction.

Data Analytics

Leverage the power of data analytics for business intelligence or to help users make data-driven decisions.

Machine Learning

Develop apps that learn from user behavior and adapt to provide a more personalized experience. 

Decision Support Systems

Build addictive products that provide users with tools and information to help them make better decisions.

Saving 2 hours daily: efficient AI & low-code accounting automation

We’ve helped our finance specialist get rid of daunting bookkeeping tasks and save her up to 2 hours every day with AI & low-code.

Read the case study

Health Folder: Your AI-based digital medical documentation folder

Discover how Health Folder revolutionizes medical documentation management with its AI-powered mobile app built using low code.

Read the case study

How AI will benefit your product

An impressive 83% of companies are making it a priority to include AI in their strategies.
Implementing artificial intelligence in product development is becoming a norm. Here’s why:


AI examines user data to provide personalized & engaging experiences.

Improved accuracy

AI analyzes data with greater accuracy and speed than humans.

Increased efficiency

AI automates repetitive tasks, saving time and reducing costs.

AI product development process

Our approach to building AI-driven products ensures maximum efficiency.



  • Competitor Research
  • UX Research


  • Testing and matching available AI tools with your project
  • Analyzing available data and potential data sources
  • Creating the Proof of Concept


  • Defining your product roadmap
  • AI model training & development

Deliver & Scale

  • DevOps architecture
  • Product development
  • Connecting the AI model to your product
Pragmatic Software Developer at Work

Use cases

The applications of artificial intelligence are endless. Check examples of products you can create with our custom AI solutions.

Optical Character Recognition + Recommender Systems

Industry: Digital Health
Use optical character recognition to enable users to scan their medical test results. Process the information to give users physical checkup suggestions.

Pose Estimation + Supervised Learning

Industry: Sports Tech
Create an app that can tell if you're performing an exercise correctly. Use AI to detect and track the position of your body and train it on what correct and incorrect form looks like for each exercise.

Audio Recognition + Natural Language Processing

Industry: EdTech
Use audio recognition to convert users’ speech into text. Analyze it with NLP solutions to provide users with feedback on pronunciation, intonation, and grammar.

Report Generation + Data Visualization

ndustry: FinTech
Create a business intelligence app that automatically generates reports and visualizations based on user data, providing insights and recommendations.

ChatGPT integration

Industry: any
Build a first-class bot that answers customers' questions in no time. Enhance user experience & make them stick with your product.

Active Learning + Predictive Analytics

Industry: Recruitment
Develop an HR app that uses active learning and predictive analytics to identify top-performing candidates and improve the hiring process.


Have questions about AI product development? Ask AI! So did we.
We reached out to one of our AI buddies, and here are its answers.

What is artificial intelligence?

AI, or artificial intelligence, refers to the development of algorithms and computer programs that can perform tasks that typically require human intelligence, such as recognizing patterns, understanding natural language, and making decisions. AI development can be broken down into several categories, including machine learning, natural language processing (NLP), predictive analytics, deep learning, neural networks, computer vision, and image recognition. Each of these categories involves different techniques and approaches for developing AI algorithms and programs.

Machine learning, for example, involves training algorithms to learn from data and make predictions or decisions based on that data. This approach is often used in applications such as recommendation systems and fraud detection. Natural language processing (NLP), on the other hand, involves teaching computers to understand and interpret human language. This is often used in applications such as chatbots and virtual assistants.

Predictive analytics involves using statistical models and data analysis techniques to make predictions about future events. Deep learning is a subcategory of machine learning that involves training artificial neural networks to recognize patterns and make predictions based on that data. Computer vision and image recognition involve teaching computers to recognize and interpret visual information, such as images and videos.

In order to develop custom AI solutions for businesses, algorithm development, data modeling, and big data analysis are critical components. These techniques enable developers to build algorithms that can learn from large amounts of data and make predictions or decisions based on that data.

Cloud computing and API integration are also important in AI development, as they enable businesses to access and process large amounts of data quickly and efficiently.

What data is used for building AI products?

Data is a critical component in building AI products. AI algorithms rely on data to learn and improve over time, making the quality and quantity of data used in AI development crucial to the success of the product.

The type of data used in building AI products depends on the specific application of the product. For example, if building an image recognition AI product, the data used would be image data. If building a natural language processing artificial intelligence product, the data used would be text data.

To build effective AI models, a large and diverse dataset is typically required. This dataset needs to be representative of the problem being solved and should be collected from various sources. The data should also be preprocessed, which may involve cleaning, normalizing, and transforming the data to make it suitable for analysis.

In addition to the data used to build the AI model, there is also data generated by the AI product during its use. This data can be used to improve the AI model over time by providing more relevant and up-to-date data for analysis. This process of continuously improving the AI model is known as "machine learning" and is a critical component in building effective AI products.

How is AI app development different from non-AI software development?

AI app development differs from non-AI software development in several ways. While traditional software development involves writing code that follows a set of rules, AI app development involves training algorithms to learn from data and improve their performance over time. AI app development requires large amounts of data and sophisticated algorithms to train the models.

One of the benefits of AI app development is that it can enable machines to learn from experience and adapt to changing circumstances, which can lead to better outcomes. However, AI app development can be more complex and time-consuming than non-AI software development due to the need for large amounts of data and sophisticated algorithms.

Another difference between AI app development and non-AI software development is the cost. AI app development can be more expensive due to the need for specialized talent, hardware, and software. However, the benefits of AI can outweigh the costs for businesses that implement it strategically. AI can provide a competitive advantage by enabling businesses to automate tasks, improve decision-making, and gain insights from data. In addition, artificial intelligence can help businesses create personalized experiences for customers, leading to increased satisfaction and loyalty.

Non-AI software development, on the other hand, is focused on creating software applications that follow a set of predetermined rules. This approach may be more suitable for simpler applications that do not require the use of artificial intelligence. Non-AI software development may be faster and less expensive than AI app development because it involves writing code that follows a set of rules rather than training algorithms to learn from data.

In conclusion, the choice between AI app development and non-AI software development depends on the needs and goals of the business.

What is AI good for?

AI is a powerful tool that can provide many benefits for businesses, including personalization, automation, and improved decision-making. However, it is important to carefully consider when and how to use AI in order to maximize its benefits and minimize its drawbacks.

AI is well-suited for applications that involve large amounts of data, complex decision-making or require a high degree of personalization. For example, AI can be used to build chatbots that can interact with customers and provide personalized recommendations based on their preferences and behaviors. AI can also be used to automate tasks such as data entry and analysis, freeing up employees to focus on more strategic tasks.

However, AI may not be the best choice for applications that do not involve a significant amount of data or require simple decision-making. In addition, the quality of the data used to train AI models is critical, as dirty or biased data can lead to inaccurate or unfair predictions.

Therefore, businesses should carefully evaluate their needs and goals before deciding to invest in AI development. They should consider factors such as the amount and quality of their data, the complexity of their decision-making processes, and the potential benefits and drawbacks of implementing AI.

How can implementing AI solutions into your startup product let you achieve your business goals?

Implementing AI solutions into your startup product can help you achieve your business goals in several ways. Firstly, AI can automate repetitive tasks, allowing your team to focus on more complex and strategic initiatives. This can help you save time and reduce costs, ultimately increasing your efficiency and productivity.

Secondly, AI can help you gain insights from your data, allowing you to make data-driven decisions and improve your decision-making processes. With AI technologies such as machine learning and predictive analytics, you can analyze large volumes of data and identify patterns and trends that would be difficult for humans to detect on their own.

Thirdly, AI can help you create personalized experiences for your customers. By using AI technologies such as natural language processing and computer vision, you can analyze customer data to better understand their needs and preferences and provide them with personalized recommendations and support.

Overall, implementing AI solutions into your startup product can help you achieve your business goals by increasing efficiency, improving decision-making, and providing personalized experiences for your customers.

What is the role of an AI development team in creating custom AI solutions for businesses?

An AI development team is a group of skilled professionals, including data scientists and AI developers, who work together to create custom AI solutions for businesses. Such specialists not only know how to leverage artificial intelligence; they know how to leverage AI in software development. AI solutions are built using machine learning algorithms that are trained on large amounts of data to recognize patterns and make predictions. 

Data science plays a critical role in this process, as it involves gathering and cleaning data, performing exploratory analysis, and selecting the most appropriate algorithms to use. AI software development companies specialize in building these custom solutions, and they have the expertise and experience necessary to deliver high-quality, effective AI products. 

By partnering with an AI development company, businesses can leverage the power of AI to achieve their business goals, such as improving customer experiences, increasing efficiency, and reducing costs.

Work with the best


The years we’ve been on the market

0 +

The number of specialists on board

0 M$+

The revenue our products generated

Let's talk

We’ve got answers on anything connected with software development.

Ask a question

You can ask us a question using the form below. We will respond as soon as possible.

Schedule a meeting

You can also schedule an online meeting with Wojciech, our Senior Business Consultant.

wojciech knizewski portrait
Wojciech Kniżewski

Senior Business Consultant

8 out of 10

founders who contacted us wanted
to work with our team.

Trusted partner


You are just one click away from receiving our 1-min business newsletter. Get insights on product management, product design, Agile, fintech, digital health, and AI.


Pragmatic times Newsletter