HAVE A CONVERSATION WITH AN EXPERT
Krasimira Bozhanova
20.8.2024
Retrieval Augemented Generation, or simply RAG, is being thrown around more and more these days. We see it in presentations, we hear about it at the watercooler, we even have people apologizing for coining the acronym “RAG” on social media.
It’s starting to get to that point of super saturation and overuse that you may be doubting what you know about RAG or how we can use it. That’s why we think it’s always best to get your information from the source, from the people that are dealing with the technology on a day to day basis – bringing it to life in our workplaces.
In this quick dive, we were able to catch Solutions Architect at Ontotext, Krasimira Bozhanova, on her way to work to ask her a few questions about herself, her work, and RAG.
Let’s get to know Krasimira!
Krasimira Bozhanova
Solutions Architect at Ontotext
Krasimira Bozhanova is Solutions Architect at Ontotext. Based in Sofia, Ontotext offers a range of techincal solutions in data management including GraphDB, Ontotext Platform, Ontotext Metadata Studio, and Ontotext Refine. Krasimira graduated with a Master’s degree with a focus on data mining and information retrieval from Sofia University.
Tell us a bit about your educational and career background.
I started my educational journey with a Bachelor’s degree in Computer Science from Sofia University. It was during my Masters studies that I delved into the world of Machine Learning (ML), focusing on data mining and information retrieval. This experience sparked a deep passion within me, particularly in exploring the synergy between these technologies and knowledge graphs. Soon after completing my studies, I eagerly joined Ontotext to further immerse myself in this fascinating field.
Tell us a bit about your current role.
Navigating through various technical positions in the company, I now hold the role of Solutions Architect within the Solutions team. I am responsible for designing how the Ontotext products are integrated in client environments and what tailored solutions we can provide on top to ensure the client needs are properly addressed.
What is your experience and/or perception of the GenAI boom?
Ontotext brings a wealth of expertise in Natural Language Processing (NLP) paired with knowledge graph construction. These fields have seen rapid advancements in recent years, greatly propelled by the innovation of GenAI. This experience has allowed me to witness firsthand the transformative impact of the GenAI boom on both my life as a Solutions Architect and the lives of knowledge workers.
What applications have you begun to use in your own team?
I am actively involved in driving our research initiatives, leading to the infusion of cutting-edge innovations into our products – GraphDB and Metadata Studio. Our focus lies in conducting research based on real-life use cases, particularly in the area of integrating GenAI and Knowledge Graphs to enhance the capabilities of both technologies.. For example, to improve how GenAI technologies are being integrated into actual production environments or how various Knowledge Graph tasks can be enhanced with the help of GenAI.
Where do you see these technologies going in the next couple of years?
In the upcoming years, I see great potential in enhancing the experience of querying a Knowledge Graph, but also making the Knowledge Graph modelling and building a lot easier – which, I believe, will lead to the increased adoption of Knowledge Graph technologies in general.
Want to hear more about what Krasimira has to say about RAG?
This interview was just a teaser. Check out our recorded webinar that features Krasimira and Márcia R. Ferreira of SWC to find out how to increase efficiency by up to 20% with Graph RAG!
Watch the recorded webinar