Service Description
AI solutions in a corporate environment, digital transformation of work processes and increasing individual and team competitiveness It includes workflow analysis to identify suitable AI applications, create a training program for the team, implement good practices, and test the results. The goal is an efficiency and plan for sustainable implementation of AI in the organization.
Health data verification analysis A service that helps organizers assess and maximize the value of their data by mapping existing data, assessing its quality and accessibility, and identifying opportunities for improvement and innovation. Through structured workshops and targeted analysis, this engagement identifies strengths such as reliable, high-value datasets and robust governance practices, while pointing out weaknesses such as quality gaps, integration issues, or limited availability. The process results in a priority roadmap that allows organizations to strengthen their data base, improve decision-making, and uncover actionable opportunities for advanced analytics, governance, artificial intelligence, and data-driven growth.
AI readiness assessment and opportunity mapping This service assesses an organization’s readiness to adopt AI-based decisions, focusing on data availability and quality, organizational capacity, relevance, and risk profile. It identifies appropriate low, medium, or high-risk AI opportunities and provides guidance on appropriate next steps. The service supports informed decision-making and avoids premature or inappropriate AI investments.
Machine Learning Data Preparation This service provides high-quality data processing, cleaning, and transformation for effective machine learning. Ideal for AI projects in healthcare, finance, transportation, and automation, it ensures that data is well-prepared and optimized for training machine learning models.
Ontology Development of the logical model of the data space
Graph database Installing and configuring a graph database
Data Space Repository Development Development of a model of physical data
Data Source Integration Setting the real-time data channel
Prototyping a Semantic Search Service Development of an Internet service for logical search of physical data
Development of a Pre-Trained Large Language Model (LLM) Pre-trained LLM training through logical and physical data space
LLM implementation Deploying LLMs to GPU infrastructure
Uncontrolled abnormality detection Development of an algorithm(s) for the detection of anomalies on images based on the already created gold sample of the scanned product.
Supply and distribution of the location of urban facilities This service includes analysis of the supply and demand of urban facilities and dynamic models for the distribution of locations based on the needs of citizens for 15-minute walking access to kindergartens, schools, health centers, offices, sports facilities, parks, etc. The analyses are based on a pedestrian network, which is transformed into a graph for the application of crossing algorithms.
Walking accessibility This service applies the concept of a 15-minute city and introduces an accessibility index that assesses residential access to points of interest (POIs) by incorporating diversity metrics, including the Shannon and Simpson indices. Sidewalk infrastructure and pedestrian network are accessed through weighted points of interest to measure pedestrian accessibility. By defining a sustainable urban environment in terms of accessibility, POI saturation, and uniformity, the service provides a reliable tool for assessing the compliance of urban neighborhoods with the 15-minute city concept.
Generating urban “what if” scenarios This service involves generating reusable “what if” scenarios, allowing planners to interactively create, modify, and test semantically rich, context-conscious urban environments with minimal manual effort. Scenarios are analyzed to derive KPIs, supporting evidence-based decision-making, and expanding stakeholders’ ability to explore diverse opportunities. The service combines creativity with analytical precision, including an assessment of execution efforts, thus linking digital exploration and real-world urban transformation.
Advanced Urban Data Query Advanced query services unify access to diverse urban datasets through reusable, AI-based interfaces. The data access layer abstracts the differences between relational, document-oriented, and graph databases, while a natural language interface powered by LLM and Retrieval-Augmented Generation (RAG) translates user queries into structured queries to a database. This will allow both experts and non-technical stakeholders to analyze complex geospatial and simulation data intuitively, reducing barriers to acceptance.
Air Quality Forecast The air quality forecasting service uses real-time sensor data and advanced machine learning models to provide accurate, future-oriented insights into environmental conditions. Through continuous analysis of input data such as particulate matter, gas concentrations, temperature, and humidity, models learn complex types and trends that affect air quality levels. They adapt over time as new data is collected, allowing for reliable short- and long-term forecasts. This enables organizations, cities, and individuals to make proactive decisions, reduce health risks, and respond effectively to changing air quality conditions.
Urban Planning Analysis This service provides data-driven insights to support planners, municipalities, and developers in creating sustainable and efficient urban environments. Using spatial data, predictive models, and visualizations, it enables smarter decision-making and strategic development. The service improves infrastructure investment decisions, increases the resilience and stability of cities, and reduces the risks associated with poorly planned urban expansion.
Climate simulations This service includes the design and execution of high-resolution urban climate simulations and scenario-based urban analysis. The results of the simulations can be integrated into GIS platforms (QGIS, ArcGIS) for spatial analysis and land use processing, as well as to support data-driven decision-making. Climate simulations will be performed using the Weather Research and Forecasting (WRF) model, which is an advanced numerical weather forecasting system and atmospheric simulation widely used for research and operational applications.
Airflow, ventilation and internal environmental analysis Computational fluid dynamics (CFD) simulations are used to analyze airflow and ventilation behavior in industrial indoor environments, taking into account the availability of production equipment, ventilation system layout and operating conditions. The analyses support the identification of areas with unfavorable air circulation, limited ventilation efficiency, or potential accumulation of air pollutants.
Preparation and modelling of traffic and environmental data Support in the digitalization of infrastructure – structuring and processing of geospatial data for the digitalization of street infrastructure. Integration of dynamic traffic data (with priority of TomTom) and municipal sensors with real-time environmental data (e.g. airbg.info) to build the information base of Digital Twin.
Data Analytics and Machine Learning for Traffic Modeling Application of machine learning (ML) and agent-based analytics to enhance and refine classic transportation engineering models, including flow pattern analysis, anomaly detection, modal separation estimation, and dynamic calibration using real-time traffic data (e.g., TomTom, sensors).
Modeling the correlation between traffic and environment Develop sophisticated analytical modules to isolate the specific impact of traffic on air quality from other factors such as household heating or weather conditions. Establish a “Green KPI” system to monitor and ensure environmental outcomes, such as reduced emissions and optimized flow.
Simulation and scenario analysis support Provide simulation logic for neighborhood-level “What if” scenarios. Feed simulation data in Unity-based 3D/VR environments, allowing experts to validate the safety and visibility of proposed infrastructure changes.
AI Act Preparedness Support This service supports organizations in understanding and implementing regulatory and governance requirements related to the deployment of AI in accordance with the EU Artificial Intelligence Act. It includes a classification of AI risks, governance guidelines, basic compliance roadmaps, and advisory support for the responsible use of AI. The service focuses on operational readiness rather than legal interpretation.
AI Detection and Regulatory Testing This service offers a lightweight proof-of-concept/demonstration activities combined with pre-AI risk classification and regulatory testing. It allows organizations to explore AI use cases on standard platforms, assess feasibility and identify regulatory implications at an early stage, for example in terms of data governance and governance. Based on the results, organizations are guided by appropriate pathways – continuing deployment, targeting AI Factory services, or preparing to enter a regulatory AI sandbox.
AI and scalable AI training Training in practical applications of AI, machine learning, and deep learning, including scalable AI approaches.
E-Transformation and Digital Leadership Training The training is focused on organizational change and the management and leadership aspects of digital transformation.
Levels 1, 2 and 3 of Artificial Intelligence Regulatory Literacy Training: Basic E-Learning Training Responsible use of AI, AI Act fundamentals, risk classification and governance principles, supporting informed and compliant adoption of AI.