As organisations increasingly seek practical, scalable AI applications that deliver measurable business impact, Qualco Technology is advancing its AI-first strategy through a new generation of enterprise AI solutions.
In his interview with “Naftemporiki”, Alexandros Tzitzeras, Senior Director of AI & Analytics at Qualco Technology, discusses with Letta Kalamara how the company is embedding AI into the core of business operations, the market demand driving its new Data, ML & Agentic AI suite, and the future of AI adoption across industries.
Qualco Technology has emphasised its strong commitment to evolving into an “AI-first” company. What is your approach to AI?
Our approach is based on the belief that artificial intelligence should not operate as a standalone tool, but rather be embedded at the core of our products and services. We focus on practical applications that address real business needs, aiming to improve decision-making, execution speed, and the overall user experience.
The solutions we develop integrate advanced AI capabilities directly into enterprise workflows, enabling organisations to operate more efficiently by delivering greater accuracy and speed in real time.
The real challenge lies in transforming insights into automated actions that support operational decision-making. This is precisely where we invest: in AI-driven systems that move beyond theoretical use cases and dynamically support the day-to-day operations of organisations.
At the same time, we ensure that AI operates within a clear governance and control framework. Transparency and the ability for human intervention where required are core principles of our philosophy.
Your 2026 product portfolio includes the Data, ML & Agentic AI suite. What market need does this new solution address, and what differentiates it from competitors?
Today, organisations are seeking ways to leverage large volumes of data with speed, consistency, and measurable outcomes. Businesses already use numerous technology tools; however, as these systems are often disconnected, they tend to operate in silos and fail to facilitate effective action.
This is exactly the gap our new Data, ML & Agentic AI suite is designed to bridge. It covers the entire operational workflow, from data and predictions to execution, unifying data, analytics, machine learning, and AI capabilities within a single environment. Rather than being limited to analysis alone, it enables organisations to instantly convert data into business action through automated processes operating in real time.
The suite has been designed for seamless integration and interoperability, both with existing Qualco Technology solutions and with third-party systems, enabling rapid adoption without requiring complex infrastructure changes.
Which customer segments is Qualco Technology targeting with its new AI product portfolio?
Qualco Technology’s new AI product portfolio is aimed at organisations seeking more effective ways to utilise their data.
It targets businesses operating in demanding environments with complex processes, where fast and accurate decision-making is critical, as well as organisations aiming to significantly reduce operational costs and improve efficiency.
Our modern Agentic AI solutions are now relevant beyond the financial ecosystem, including businesses with clear needs for advanced analytics, forecasting, AI agents, chatbots, process automation, real-time decision-making, and optimisation of complex workflows.
The true value of AI lies in its ability to meaningfully improve day-to-day business operations. That is why our philosophy focuses on building solutions that integrate effectively into an organisation’s enterprise ecosystem, supporting both strategic decision-making and operational execution at scale.
Which sectors of the economy are showing the greatest momentum in AI adoption, and how do you expect the market to respond to Qualco Technology’s new solutions?
The strongest momentum in AI adoption is currently observed in the financial sector, particularly in areas related to credit processes, risk assessment, and customer operations, where rapid data analysis is essential for both efficiency and competitiveness.
At the same time, industries with a strong need for process automation are demonstrating increased demand for Agentic AI solutions that support real-time decision-making.
Over recent years, the market has shown a clear shift away from large-scale, multi-year transformation projects towards more targeted, modular, and rapidly deployable solutions that deliver measurable value.
The response to our new solutions has been highly positive, as businesses are under increasing pressure to improve operational efficiency and respond immediately to growing market challenges.
Our approach, combining AI capabilities within a unified environment, aligns directly with this new business reality and the evolving needs organisations face daily.
What level of investment is required from companies to integrate AI products, and where do the main implementation challenges lie?
Adopting AI solutions no longer requires the large-scale investments associated with previous years. Our approach is based on a SaaS (Software-as-a-Service) architecture, enabling businesses to integrate our solutions into their existing systems without significant investment in new infrastructure, system replacement, or extensive changes to their current technology environment.
One of the key advantages of the new Data, ML & Agentic AI suite we recently introduced to the market is its ability to operate either independently or in combination, allowing organisations to tailor adoption according to their specific needs.
In parallel, onboarding can be completed within as little as a single day, while the first measurable results can emerge within a very short timeframe, even within days or hours, provided that relevant and usable data is available.
However, the biggest challenges surrounding AI implementation today are not necessarily technological. The real difficulty lies in how AI is meaningfully integrated into business processes and decision-making, which is closely linked to the availability of high-quality data. In many cases, businesses either lack access to sufficient data or the data available is unreliable and therefore difficult to utilise effectively.
Equally important is organisational adaptation to a new operating model, as broader business transformation requires a culture of adaptability, a clear strategy, and effective change management across all levels of the organisation.
What are the main areas of focus for the company’s R&D in support of its AI product strategy?
Qualco Technology’s R&D focuses on developing AI solutions capable of operating effectively in real-world, demanding business environments. For us, the value of AI lies in its ability to contribute meaningfully to everyday business operations and deliver measurable results.
A central pillar of our R&D strategy is the unification of data, analytics, decisioning, and operational execution within a single system, alongside the development of architectures that enable seamless connectivity across all levels. This allows businesses to collect and analyse data in real time and make immediate decisions.
At the same time, reliability and responsible AI operations remain top priorities. We invest heavily in explainability, enabling our systems to clearly and transparently explain how decisions or predictions are reached, as well as full decision traceability throughout every stage of AI operations.
We also focus on governance mechanisms that ensure control and transparency, including governance frameworks, Responsible AI mechanisms, and human-in-the-loop capabilities, ensuring that artificial intelligence always operates within a clearly defined framework of oversight and business accountability.
Ease of integration and rapid time-to-value are equally important priorities, allowing our solutions to be adopted quickly and begin delivering business value within a very short period.
Our solutions are built on scalable enterprise architectures designed to support large volumes of data, heightened security requirements, and complex operational workflows. We are confident that the future of AI belongs to solutions capable of combining advanced technology with enterprise-scale operational capabilities.
This inverview was originally published by Naftemporiki
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