We work with companies, startups, technology providers, research organisations and European R&D consortia, covering the path from problem and user needs to product definition, prototype or MVP, validation and the evidence needed to decide what should advance.
Between an idea, a research result or a promising technology and a product that could be adopted lies a stretch few plans protect: deciding what the product actually is, making it tangible, testing it with the people who would use it, and gathering evidence that holds up.
That stretch is our remit. We work in it so the next investment decision rests on evidence rather than intuition, whether the answer turns out to be advance, modify, prioritise, scale or reconsider.
We also research it. Our open R&D line asks why patients abandon digital health interventions and whether calibrating information dose per person can change that. See the R&D Lab.
"Industrial AI rarely fails for technical reasons. It fails for organisational ones." Alan Menk · ESTEP AI-4-Steel Workshop, Leoben, April 2026
We work alongside internal teams, technology providers, research groups, innovation consultancies and consortium coordinators. Our contribution starts at the first framing of the problem, not once the specification is already written.
Understanding the problem, the users and the use cases, then turning them into a product proposition specific enough to be built and argued for.
Making an idea, a need or a technology tangible, so it stops being a discussion and becomes something people can react to.
Hypotheses, user research, experiments and metrics, run to produce evidence that stands up, including when that evidence is negative.
Identifying which AI use cases are genuinely worth pursuing, designing them around the people who have to trust the output, and testing whether they hold.
Our approach is a sequence shaped by our founding team’s experience across real innovation and R&D projects. Every stage exists so the next decision is better informed than the last.
Understand the problem, the users, the assumptions and the use cases that actually matter.User research · Voice of Customer · stakeholder discovery · process analysis · data archaeology · Opportunity Solution Trees
Turn the opportunity or the technology into a concrete product proposition.Value proposition · use cases · requirements · UX · AI use cases · scope and prioritisation
Make the proposition tangible, as a prototype or an MVP, so that it can be tested.Prototypes · MVP definition · technical feasibility · TRL positioning
Test the assumptions with users, metrics and real evidence.Hypotheses · user testing · pilots · usability · success metrics · evidence reporting
Use the evidence to determine the next justified step.Advance · modify · prioritise · scale · reconsider · exploitation and adoption readiness
Evidence is not generated only to prove that an idea works. It exists so that an organisation can decide whether an initiative should advance, be modified, be prioritised, be scaled or be reconsidered. A result that closes a line early is worth as much as one that opens it, and costs far less than finding out two years in. Adoption and exploitation may follow: what we commit to is preparing the ground for that decision and evidencing it, not guaranteeing the outcome.
Figures from European and corporate programmes delivered by our founding team in previous and current professional engagements, before and outside Vuola Consulting, S.L. They evidence capability, not Vuola’s own delivery history. Sources: EU Funding & Tenders Portal (project 101080048) and the smartCARE Final Blueprint report.
Vuola Consulting is a newly established technology company, built on the previous experience of its founding team across European R&D, digital health, industrial AI and technology innovation. The initiatives below are that prior experience, not engagements delivered by Vuola.
PhD, with research in intelligent and recommender systems. Author of the RIVER framework paper for industrial AI. Product leadership and technical work-package experience in international consortia (RFCS Clean Steel, EU4Health).
Specialist in data architecture and systems integration, with over ten years in complex production environments and corporate infrastructure.
We focus on one stretch of the journey: turning a problem, an idea or a technology into a product proposition that can be prototyped, tested and evidenced. We do not coordinate projects, we do not assemble consortia, and we do not claim to carry a product to market for you. We join forces with R&D&I consultancies and coordinators, contributing product and technical rigour without overlapping their work. See exactly where we stop →
Choose your starting point to define the next steps:
Tell us the idea, the technology or the prototype. We will set out what needs testing and what evidence would settle it.
Send us the topic or the call. We will propose the role we would take, the deliverables and the effort allocation.
Set out your innovation challenge or territorial project. We will design the approach and the validation model.
