Why do we do research?

In our quest to lead in AI innovation, we not only harness state-of-the-art technologies but also pioneer the development of new ones, venturing into unexplored territories of artificial intelligence. This relentless drive propels us beyond conventional boundaries, enabling us to solve complex challenges more effectively across various domains. Our commitment to staying at the forefront of AI research ensures continuous growth and exploration, as we shape the future of technology and unlock potential yet to be fully understood. Through this approach, we're not just adapting to the evolution of AI; we're defining it.

How we do research?

Our research process is like that of universities or other research institutes. We start by reviewing academic literature and identifying state-of-the-art for our current challenges. We are particularly interested in solutions that show potential to be further developed and scaled to handle more difficult problem instances. With the most promising approaches we run an algorithm engineering loop, where we implement and then repeatedly evaluate, profile, analyze and optimize the algorithms until they are capable of handling real industry scale problems.

Finally, we, on top of implementing and integrating our solutions into our platform and products, also publish them as patents and scientific publications.

What is current focus?

Our current focus is on creating methods to learn action models from logs for enhancing process automation, including software testing. By capturing changes in dynamic systems, we're able to automatically generate models that detail all valid transitions, significantly streamlining tasks such as test generation, planning optimization, and system verification. These efforts lead to the synthesis of symbolic action models, which are instrumental in automating system validation and reducing the associated effort. For more insights and detailed descriptions of our work, explore our research blog posts, patents, and publications through the provided links.

Research team

The core Filuta research team consists of four senior scientists with strong academic background (PhD in Symbolic AI), expert knowledge in usage, design and development of AI systems and experience with industrial applications of such systems.

Besides the core team, we have an intern and two senior scientific advisors.

Highlights & Achievements

We recently published three preprints about our ongoing research in the areas of:

We presented the prototype version of our Filuta platform at the ICAPS 2023 Conference. It was received very well by the research community, and we achieved the 2nd place in best System Demonstration Awards.

Furthermore, we attended and presented the Filuta platform prototype at two additional conferences: SAT 2023 and SoCS 2023. At both conferences we received a lot valuable feedback and encouragement for our work.

Our talents

Colaboration is a key

We actively collaborate with the scientific community on multiple levels. As already mentioned, we attend scientific conferences, where we publish our results. Additionally, we provide financial donations to conferences (ICAPS, SoCS, SAT) and competitions (International SAT Competition). Finally, we started organizing a new workshop on Composite AI at the European Conference on Artificial Intelligence (ECAI) to nurture interest and collaboration in this field.




We were supported by the system project Technological Incubation



The AIPlan4EU project is funded by the European Commission – H2020 research and innovation programme under grant agreement No 101016442

© 2024 All Rights Reserved. Filuta AI.
  • Icon