Predicta

💎 The Idea: Predicta (API as a Service)

The Problem: For industrial giants and energy companies, water is not just a resource, it is the lifeblood of production. However, water stress is often difficult and costly to predict. Most companies do not have the tools to understand whether their power plant or factory will be able to operate in 5-10 years in a particular region. Floods, contamination, and other causes of damage, lead to production shutdowns, costing billions of dollars in losses that are difficult to insure without accurate data.

The Solution: Predicta is a predictive API service that helps production facilities, insurers and developers assess the risks of water stress. Our platform combines satellite data with historical archives and climate models (roadmap). We provide more than just a map, but a 5-10 year forward trajectory that allows businesses to plan investments, adapt infrastructure and minimize financial risks.

🛰️ EU Space Technologies at the Core

Our platform uses the full range of the Copernicus program to create an accurate "digital twin" of water resources:

• Sentinel-2 (Optical Monitoring): We use multispectral imagery to calculate the NDWI (Water Depth Index). This allows us to accurately track the area of water surfaces and see the gradual "squeezing" of rivers and reservoirs around industrial facilities.
• Sentinel-3 (SLSTR Thermal & Altimetry): We measure water surface temperature and its rise. Rising water temperatures are the first indicator of future "stress" that affects the efficiency of power plant cooling systems.

💧 EU Space for Water: A Strategic Asset

We turn space technology into an economic shield. Our project addresses the challenge of analysing and managing risk.

1. For businesses: It is a tool for longevity and strategic planning.
2. For insurers: It is objective data for calculating insurance premiums.
   
   

👫Our technical and business core:

• Julian Drohomirecki (Solution Architect & Lead):
  Solution Architect focused on data, AI, and scalable systems. Currently working at a German cybersecurity company, where he designs infrastructure, monitoring systems, and machine learning solutions for real-world applications. He has a proven hackathon track record, achieving top placements (3rd place at the Critical Infrastructure Hackathon, 7th place at EUDIS 2025), and experience across diverse, fast-paced challenges. Particularly interested in deep learning and building high-impact solutions under pressure.

• Michał Jastrzębski (Backend & Data Engineer):
  Experienced in applied mathematics and algorithm design for logistics systems. Studied theoretical mathematics at Adam Mickiewicz University in Poznań. Currently works as a Data Engineer at Dimark IT, focusing on baggage flow prediction and response systems in airport Baggage Handling Systems. Participated in multiple hackathons, including: EUDIS 2024 (Machine Learning for defense data extraction – distinction) Hack of Tomorrow 2025 (Blockchain for secure space communication – 2nd place) QLFuture 2025 (Quantum Computing for financial risk management) In this project, responsible for spatio-temporal data aggregation, preprocessing, backend architecture, and API development. Designs scalable and modular data pipelines tailored to the project's business model.

• Michał Falbogowski (Math Modeling):
  Specialist in applied mathematics, statistics, data analytics, and physics-based modeling. Responsible for mathematical modeling, statistical analysis, and simulation components of the project. Holds a Bachelor's degree in Mathematics (Data Analysis and Visualization specialization) from Adam Mickiewicz University in Poznań and is currently pursuing a Master's degree in Pure Mathematics. Completed a summer internship at Baloise in Hamburg, gaining experience in risk modeling within the insurance sector.

• Roman Horbach (Tester & Debugger):
  Computer Science student and experienced Python and C++ developer. Specializes in debugging and optimizing complex systems, ensuring reliability and high performance. AI/ML engineer with a strong background in backend technologies. Experienced in building intelligent systems, including real-time gesture recognition using LSTM and OpenCV. Works with Django and FastAPI to deliver stable server-side solutions. Plays a key role in testing, debugging, and ensuring system robustness.

• Diana Buriak (Frontend Developer):
  Developer with a strong foundation in Python and DevOps, combined with 2 years of hands-on frontend experience. Understands the full lifecycle of application development. Responsible for the client-side of the project, focusing on delivering a seamless user experience while maintaining scalability and smooth deployment from the early stages. Specializes in user interface design and data visualization. Develops the interactive dashboard and map-based interface that enables users to easily interpret and act on water risk data.

• Sofiia Donets (Business & Product Lead):
  Second-year Computer Science student at DSW University of Lower Silesia, specializing in Application Engineering and Cloud Systems. Active member of the Network Masters student organization. Developing expertise in marketing through practical experience. Strong communication and interpersonal skills, with a proactive approach to challenges. Responsible for business strategy, product direction, and project coordination. Conducts market research, defines the business model, identifies customer needs, and ensures alignment between technical development and real-world applications. Also leads pitch preparation.