Reliable data, concrete use cases and multidisciplinary expertise to design AI applications that are useful to companies, healthcare, public services and territories.
Technoscience’s Artificial Intelligence Competence Centre develops projects together with companies, universities and researchers. We start from the problem to be solved, the availability and quality of the data, and the processes into which the solution must be integrated.
We approach research, prototyping, training and consultancy with attention to verifiability, safety, data governance and organisational impact. The objective is to move from experimentation to tools that can genuinely be adopted.
We develop applied research projects in machine learning, generative systems, predictive analytics and decision support. Every experiment starts from a defined problem, uses verifiable metrics and addresses data quality, model limitations, security and operational integration from the outset.
Data comes before the model. We map sources, formats, completeness, quality, bias, permissions and responsibilities to build a data-readiness and governance plan. This reduces errors and costs, improves reproducibility and creates reliable foundations for automation and AI.
We build prototypes and proofs of concept to test feasibility, performance and use-case value with controlled investment. We test user experience, integration, operational risks and success metrics, producing actionable evidence for scaling decisions.
We design learning paths for managers, professionals, technicians and developers who need to understand or use AI. Content combines principles, tools, exercises, sector-specific cases, responsible use and outcome assessment, calibrated to participants’ starting skills.
We help organisations identify the highest-value use cases and define a realistic roadmap. We assess processes, data, technology, skills, risks and organisational impact, supporting choices between in-house development, partnerships, solution procurement and progressive experimentation.
We apply AI and data science to health, biotechnology, finance, industrial automation, public services and territorial systems. Multidisciplinary work adapts methods and indicators to each context while meeting requirements for reliability, transparency, data protection and sustainable adoption.
Do you have a process, information asset or use case to assess? We can build an initial technical and operational analysis.