From the early Eliza chatbot to modern generative AI solutions, what was once a technological curiosity is now a boardroom priority. At Intellias, we help our clients adopt and adapt generative AI (GenAI) capabilities to work smarter.
Our generative AI services turn vast data into focused intelligence, automate complex workflows and build differentiated experiences for your employees and customers. We don’t just deploy AI— we place generative AI where it’s most effective, delivering productivity gains, ROI and secure, scalable innovation.
We approach AI by helping you transition from isolated use cases to operational generative AI solutions. Together, we analyze IF and HOW generative AI can improve your business processes. Then, we create a flexible roadmap that allows for gradual improvements and lays a solid data foundation for different AI models. With this, you can adapt and turn AI technology capabilities into real-life applications.
Generative AI readiness evaluation
The GUARDIAN framework provides a structured approach for responsible integration of generative AI technologies, addressing the entire lifecycle from design to deployment and scaling. Our goal is to transform AI into a controlled, high-performance business asset while ensuring ethical standards and regulatory compliance.
We establish clear rules that prioritize fairness, transparency and human oversight in AI development, helping clients protect individual rights and ensure accountability.
We identify data privacy issues, compliance challenges and operational risks, combining technical assessments with insights into human impact and alignment with organizational values.
We implement detailed permission control measures to protect sensitive information in generative AI applications, ensuring that only authorized personnel can access critical data.
We practice continuous oversight and audits of AI systems to effectively identify and address emerging risks, supporting ethical management across the company.
We establish responsibility matrices across projects and evaluate AI systems for human impact, fairness and safety to reduce risks and promote sustainable governance practices.
We prioritize transparency in AI decision processes, clearly explaining how GenAI systems reach conclusions so that only reliable outputs are used to make business decisions.
We offer training programs that help teams understand generative AI’s functionality and ethical implications, fostering realistic expectations for further responsible AI use.
We provide resources to help businesses conform to AI regulations, align operations with industry standards and confidently build on their AI strategies while avoiding costly missteps.
We deliver generative AI as a service that marries industry-specific perspectives, custom-fit technical tools, a powerful partner network and responsible design principles.
Targeted AI solutions across key industries including healthcare, automotive, finance and retail
Custom solutions that comply with relevant regulations and meet international standards
End-to-end AI integration services from strategy, governance to execution across cloud, data and automation
Innovative solutions such as IntelliCopilot, IntelliAssistant and IntelliTwin maximizing productivity across all operations
23 years
industry experience
14
global locations
3k+
experts
100+
proprietary assets
Hana Rizvić
Head of AI
Hana is a data scientist with a decade of experience in the field and an AI/ML expert. At Intellias, she has developed the AI/ML practice into a separate, robust domain and a core offering. Her expertise lies in not only orchestrating and motivating teams but also in shaping forward-thinking growth strategies for businesses implementing AI/ML worldwide. Under Hana’s leadership, the AI/ML practice at Intellias continues to grow, now including GenAI offerings and a responsible AI practice which she recently launched.
With a solid mathematical background, Hana has spent her career focusing on predictive analytics and machine learning, helping clients in healthcare, energy and insurance. She holds a Master’s in Applied Mathematics from the University of Rijeka in Croatia.
Gregorio Ferreira
Head of MLOps
Gregorio is an experienced data specialist with more than a decade of experience in data architecture, AI/ML and cloud solutions. A leader in creating data-driven SaaS offerings, he combines technical acumen with strong leadership of high-performing data analytics teams.
Gregorio has championed data-centric initiatives in multiple industries while keeping an eye out for opportunities to adopt AI. He has shaped AI/ML and data science strategies for Akamai Technologies, ArcelorMittal, ABB and GE Healthcare, in addition to holding several positions in academia.
As a recipient of the Marie Curie fellowship, Gregorio dedicated four years to in-depth research of strategies for monitoring industrial conditions. He holds a PhD in advanced signal processing/ML from the Cracow University of Technology in Poland.
Vedrana Vidulin
Head of the Responsible AI Unit
Vedrana has more than 15 years of experience in data science and machine learning and holds a PhD in Artificial Intelligence from the Jozef Stefan Institute in Slovenia. At Intellias, she transforms complex data ecosystems into practical solutions for companies worldwide using machine learning, predictive modeling and data visualization. She is also the Head of Responsible AI, ensuring that AI is used in a trustworthy, safe and responsible manner.
As an academic and a data science researcher, Vedrana has particularly deep knowledge of AI/ML that places her in a unique position to formulate ethical AI policies and implement them across the organization. Through mentorship and thought leadership, she helps teams bridge the technical side of AI/ML with the company’s strategic vision, turning data into a powerful business asset for empirical decision-making.
Atina Koljevina
Head of the AI/ML Center of Excellence Unit
А research engineer with almost a decade of experience, Atina specializes in deep learning and data science. At Intellias, she continually explores innovative ways to apply AI and machine learning solutions to business challenges, working on international and interdisciplinary projects.
Her expertise includes developing deep learning algorithms for face detection and recognition, as well as leading projects on lightweight neural networks, data annotation and proof-of-concept development. She holds a Master of Science in Computer Science and Mathematics from the University of Zagreb.
Make your AI investments deliver real business value, moving beyond isolated use cases to strategic generative AI implementation
