HOW WE CAN HELP
Data is the new oil. Do you
know how to leverage it?
We can support you with AI strategy design and implementation of data science projects and AI models. We use state-of-the-art models and MLOps practices to quickly deliver working solutions. After the deployment, we can monitor the performance of the models to maintain the quality over time.
Read more about how we help our clients build classification models in our case study.
With modern AI techniques, you can achieve real-time asset monitoring, avoid unnecessary maintenance, reduce sudden breakdowns, increase asset life and prioritise maintenance. With the increasing quantity of IoT data, we can build reliable digital twins, help you optimise your operations and build a truly smart factory.
Accurate sales forecasting is crucial in business planning and risk management. It allows the efficient allocation of resources, providing the demand for raw materials, estimating revenue and planning investments. We can employ the latest forecasting frameworks and integrate various data sources, both internal (historical sales, marketing activities) and external (macroeconomic data) to improve our client’s forecasting methods. Check our case study to find out more about this solution.
Our demo: Churn prediction using AutoML on GCP and Looker dashboard
Developing smart city solutions can create value in numerous ways: increased life quality, improved infrastructure, reduced environmental footprint, water management efficiency or better traffic management. We have experience working with publicly available data streams and modelling public transportation services.
Read more about Smart City Analytics on our blog.
Debt repayment prediction
Machine learning methods could be used to classify clients that will be able to pay their debts and even predict the amount that will be repaid. Using historical data of debtors’ past payments and interactions, our team can build AI models to make individual and portfolio predictions for better decision making and business strategy. Similar techniques could be applied for credit scoring.
In challenging times, it is crucial to identify the biggest risks and understand their impact. By leveraging data science techniques, we can build simulation engines to model the behaviour of a given system in various scenarios, such as disruptions in supply chain networks, or the spread of infectious diseases like COVID–19 in cities, depending on restrictions. Simulation techniques could also be used to optimise workforce allocation.
Our demo: Modelling the spread of Covid-19
MEET OUR EXPERT
In my work, I leverage both IT skills and business knowledge to run analytics projects in various industries such as telco, retail, automotive or banking.
My experience spans from building predictive models, scaling data science teams for startups and designing digital transformations for corporations.
I have completed postgraduate management studies based on an MBA program.
Artificial Intelligence & Machine Learning
A step-by-step guide to Computer Vision AutoML in Microsoft Azure
AI and machine learning in healthcare: transforming patient care and revolutionising medical research