Artificial Intelligence

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As the Chief Executive Officer, you develop a strategic vision to improve the company’s competitiveness and create new revenue streams. You want the business to be able to analyse large amounts of data to identify patterns and trends, forecast demand,  anticipate customer behaviour, and enable the organisation to make informed business decisions.
As a Chief Technology Officer, you’re looking for the optimal technology solutions to bring the company strategy to life. Your goal is to automate routine tasks such as data processing, information entry, and customer service. This will free up employees’ time to perform more complex and creative tasks and increase their productivity.


It is worth emphasising the importance of two technologies: generative AI and decision intelligence. Early adoption of these technologies can provide a significant competitive advantage and simplify the use of AI models in business processes.

Generative AI is a subset of artificial intelligence that focuses on creating new data, whether it be text, images, video, or other formats. It uses machine learning models that are trained on large data sets to then generate new, similar data. These include:

Generative adversarial networks (GAN), where two neural networks compete with each other, one generating new data and the other trying to distinguish it from real data.
Variational autoencoders (VAE), which encode data into latent space and then decode it back, allowing new data to be generated by manipulating the latent code.
Transformers, which embody a neural network architecture that is well suited for processing sequences of data such as text.

These techniques are used to generate text, images, videos, and music. They improve data quality by pre-learning existing data, and synthesising missing data. You can use them to develop new products, they help generate ideas for products and services. One of the most famous examples of generative AI is DALL-E 2, an image generator that can create photorealistic images from a text description.

Decision Intelligence (DI) is a field of AI that focuses on helping people make more informed decisions. DI uses machine learning algorithms to analyse data, identify patterns and predict future events. It includes:

Machine learning, which involves algorithms that learn from data and can make predictions.
Optimisation, which implies methods for finding the best solution to a problem.
Risk analysis, where the probability of various events and their potential consequences are assessed.


On its own, AI can process and analyse large amounts of data much faster than humans. This allows it to be used for forecasting, identifying patterns, and making better decisions. AI can also recognise objects, faces, and other visual patterns. We use these capabilities in areas such as computer vision, biometric authentication, and autonomous vehicles. Understanding and generating human speech is used in machine translation, chatbots, and voice assistants. In hazardous and complex environments, AI can control robots to perform tasks that are potentially dangerous to humans. In tandem with humans, AI can write texts, create music and design. AI can also be used to personalise learning and provide students with individual support.
However, AI still has some limitations today, such as a lack of creativity and empathy. This means that AI cannot generate truly original ideas or understand and respond to nuances of emotional responses. In addition, it depends on data – AI can be biased if the data it learns from is not representative. At the same time, security issues may arise when working with AI. It can be used to create malware or manipulate people.

artificial intelligence risks and solutions

Effective integration of AI into business operations requires a well-thought-out strategy. Without a strategic approach, implementing AI can be risky. One recommended strategy involves identifying specific areas in the business where AI can deliver tangible benefits while ensuring alignment with overall business objectives. This is where we can be your technology partners to develop and implement a solution that can help you. Our approach in delivering project with significant AI component:


We evaluate current state (point A), the desired state (point B) in measurable, specific terms.


We assess how AI can benefit you and which type of AI would be most suitable to help you achieve your goals.


We examine the risks you may potentially face and how we can minimise them by working together.


We design, develop, and implement the solution, testing not only technical but business impact along the way.

It is worth noting that AI solutions aren't always capable to outperform human experts in terms of expertise and thought process. That's why we believe it is necessary to assess the potential value that AI can add. Critical decisions, especially those with significant consequences, should be vetted by human experts.


We apply our interdisciplinary expertise to solve a wide variety of business problems. Here are the examples of the solutions we can help you develop or improve:




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Computools shapes the future with products, services and solutions that businesses need to Unlock Tomorrow. We are a global company that delivers on the world-changing ideas that we co-create together with our clients.

Whether we’re designing customer experiences, dealing with our clients or managing our teams, we lead with empathy. Technology is for everyone, not just the geeks. That’s why we focus on using clear, intelligible language, treating every stakeholder with respect and providing support at all stages of development. By starting with a shared understanding of what makes us all human, we’re able to create the favorable conditions necessary to develop our best-in-class solutions.