Our Computer Science students use their skills to tackle real-world projects. Through prototyping they bring fresh perspectives and problem-solving to your ideas while building their craft.
We combine elements of Scrum with selected practices from Extreme Programming (XP) to create a hybrid agile development approach. This allows us to deliver high-quality software while adapting to the unique needs of each project. Our approach ensures that your project evolves through iterative cycle.
Our students can help bring your innovative ideas to life. Whether you are testing new concepts or exploring features for your future roadmap, you’ll receive a functional prototype that adds value to your development process and supports creative problem-solving.
Type of projects
Your involvement is key to the project’s success. Regular meetings, held weekly or biweekly, allow for feedback, process guidance, and progress reviews. If you wish, you can also influence the team's technical decisions and code quality management by reviewing the code produced by the team.
Working with us is simple. We welcome project proposals from companies, non-profits, research institutions and units of the University of Helsinki.
A support fee of €3,000 (+VAT) applies to companies, while non-profits and research institutions are not charged.
All work is released under an open-source licence (e.g., MIT, GNU GPL). The University of Helsinki retains immaterial rights to the software but shares them with all stakeholders in the spirit of open development.
Project periods:
For questions regarding project ideas, please contact the course instructor, Matti Luukkainen (matti.luukkainen@helsinki.fi).
Students participating in the course are Bachelor's level computer science students. They do not yet have in-depth expertise in data analytics or artificial intelligence. Therefore, projects requiring the development of AI from scratch (e.g., "develop an AI for X") are generally not suitable. However, projects that leverage existing libraries and focus on their application and integration can be well-executed by the student teams.
If you're interested in seeing an example of an AI-related collaboration, take a look at the VTT - Future Customer: simulation and prediction tool for new customers project below. This project utilized existing AI solutions and provided students with an opportunity to apply predictive analytics and simulation methods in practice.
EFICODE - Training Hub app
Eficode commissioned a student team to develop an application that simplifies training management and supports employee skill development.
The student team created a prototype that allows employees to register for training sessions, provide feedback, and suggest new training opportunities. The application provides trainers with tools to manage participant information, edit training details, and promotion. During the project, the team also explored the possibility of integrating the application with Google Calendar and Slack, as well as utilizing Google OAuth authentication to enhance the user experience (video).
ELISA - Coaching tool for Counter-Strike 2
Elisa commissioned a student team to develop a Virtual/Mixed Reality prototype for enhancing the Counter-Strike viewing experience. While designed for spectators, the project also explored AI-driven features to support professional coaching.
The student team built on previous development work, focusing on 3D visualization of game events and real-time analytics tools. The solution leveraged Game State Integration (GSI) and VR/MR technology to provide deeper insights into competitive play. The project was implemented using Unity, Python, and PostgreSQL, with Meta Quest 2/3 as the target platform (demo video).
TELINEKATAJA - Workplace safety with a multilingual mobile app
Telinekataja Oy collaborated with our students to create an easy-to-use mobile application for on-site safety assessments.
The student team delivered a prototype mobile application designed for real-time hazard assessment in industry and on construction sites. The solution offered streamlined usability, multilingual functionality, and a robust foundation for integrating into existing safety protocols (demo video).
VTT - Future Customer: a simulator and prediction tool
VTT commissioned a student team to develop an AI-driven tool for predicting customer trends and behaviors using historical data and weak signals. The project allowed students to apply predictive analytics and work with advanced simulation technologies.
The team built a web-based prototype that analyzes market data to generate future customer profiles. By inputting a company name, businesses can anticipate trends and refine strategies. The project involved AI algorithm development, data integration, and implementation using Python, JavaScript, and machine learning libraries.