Innovation in Research and Engineering Solutions (IRES)
Corporate brand
UnclaimedBelgian engineering and data-science consultancy founded in 2015 that builds decision-making tools and methodologies for environmental, safety and risk assessment, materials characterization and process optimization.
Last updated September 26, 2026
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Overview
Innovation in Research and Engineering Solutions (IRES) is a Belgian engineering and data-science company founded in 2015. According to its official website, the firm is devoted to providing decision-making tools and methodologies for environmental, safety and risk assessment, materials characterization and digitization, and process optimization. Its stated mission is to deliver world-class innovative solutions, and it describes itself as a team of chemical engineers, physicists, materials scientists and data scientists. IRES positions its work around customized, tailored solutions delivered on demand, often in the form of software tools. These tools are intended to identify possible business risks and to provide sustainable directions for clients. The company says it considers the whole lifecycle of products through a holistic evaluation of social, environmental and economic aspects based on EU standards and regulations. This regulatory-anchored, lifecycle-oriented approach is central to how IRES frames its value proposition. In terms of technical scope, IRES provides expertise and services for cutting-edge technologies including Nearly Zero Emission Buildings (NZEBs), renewable energy systems such as photovoltaics and wind and tidal turbine rotor blades, additive manufacturing, (nanoenabled) composites, and water pollution and wastewater recycling. The company also highlights collaboration with external bodies and related initiatives, positioning itself at the frontier of new technological events, emerging innovative technologies and strategic research trends. A significant part of IRES's identity is its Data Science practice, which it describes as playing a key role in exploiting data from field experts. The team works closely with engineers and materials scientists to introduce data-driven solutions, with machine learning and artificial intelligence forming a crucial part of its research. This includes an end-to-end pipeline of work spanning data collection and beyond. The company lists Konstantinos Sioutas as leader of its Data Science and Materials Science Digitization activities, with team members including Vanessa Lislevand, Panagiotis Kolozis, Christos Karounias and Dimitris Kanakis. IRES operates as a private company and is associated with Belgium. Its public footprint is relatively specialized, focused on research-driven engineering services rather than mass-market products. The firm's combination of materials science, process engineering and data science places it in the niche of technical consultancies serving industrial and research clients working on sustainability, energy and advanced materials challenges.
History
Innovation in Research and Engineering Solutions (IRES) was founded in 2015, according to its official website. The company emerged as a specialized engineering and data-science consultancy based in Belgium, built around a team of chemical engineers, physicists, materials scientists and data scientists. From its founding, IRES focused on providing decision-making tools and methodologies for environmental, safety and risk assessment, materials characterization and digitization, and process optimization. Rather than offering generic consulting, the firm developed customized and tailored solutions on demand, often delivered in tool form, with the aim of identifying possible business risks and providing sustainable directions for clients. A defining feature of IRES's approach is its lifecycle perspective: the company evaluates social, environmental and economic aspects of products based on EU standards and regulations. This positions its work within the broader European push toward sustainability, regulatory compliance and resource efficiency. Over time, IRES has extended its expertise to cutting-edge technology domains. Its website lists Nearly Zero Emission Buildings (NZEBs), renewable energy systems such as photovoltaics and wind and tidal turbine rotor blades, additive manufacturing, (nanoenabled) composites, and water pollution and wastewater recycling among the areas it serves. The company also emphasizes collaboration with external bodies and related initiatives, describing itself as part of, building upon and pushing the frontiers at new technological events, emerging innovative technologies and strategic research trends. A major pillar of IRES's development has been its Data Science practice. The company states that data science plays a key role in exploiting data from field experts, and that its team works closely with engineers and materials scientists to introduce data-driven solutions. Machine learning and artificial intelligence are described as a crucial part of the team's research, encompassing an end-to-end pipeline from data collection onward. Konstantinos Sioutas is identified as leader of Data Science and Materials Science Digitization, with team members including Vanessa Lislevand, Panagiotis Kolozis, Christos Karounias and Dimitris Kanakis. As of the available public information, IRES remains an active private company. Its history is one of steady specialization at the intersection of materials science, process engineering and data analytics, serving industrial and research clients facing environmental, safety and sustainability challenges.
- 2015
IRES is founded, according to its official website.
Products and positioning
A research-driven engineering and data-science consultancy delivering customized, EU-regulation-aligned decision tools for sustainability, safety, materials and process challenges.
Decision-making tools for environmental, safety and risk assessment
Customized tools and methodologies that identify possible business risks and provide sustainable directions.
Materials characterization and digitization
Methodologies and services for characterizing and digitizing materials, supported by data science.
Process optimization
Solutions for optimizing industrial and research processes.
Data science and machine learning pipelines
End-to-end pipelines from data collection onward, applying machine learning and AI to engineering and materials problems.
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