The solution enables the extraction of dispersed data from PDF documents and transforms it into a structured, transparent format – data that can later be used to power machine learning models and other GenAI-based solutions.

The solution enables interaction with the company’s knowledge base – it provides instant answers to questions about internal procedures, policies, or regulations – even in the case of complex queries.

A solution for call centers that converts speech to text during customer conversations. When a keyword is detected, the system displays relevant instructions or messages for the consultant.

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

We design and implement integrations that streamline data flow between applications and systems.

We consolidate data from multiple sources into one consistent and secure environment, supporting effective reporting and accurate business decisions.

We create AI solutions that support manufacturing companies in data analysis and process optimization.

Practical workshops that turn data and Artificial Intelligence into real business value.

Processing, analysis, and intelligent recommendations (including predictions) all in one place, based on large data sets.

Transition from outdated technologies to modern architectures – rebuilding applications without losing critical business logic and without interrupting system operations.

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

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

We implement intelligent solutions that maximize the potential of data – from integrating data from various sources to visual data dashboards.

We migrate between cloud and on-premises environments, and support the development of hybrid infrastructures.

We automate data processing (ETL, ELT, NiFi, Airflow), integrate data sources, and prepare them for analysis.

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

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

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