About us
Behind Rely is a team that started out as two engineers with an idea
Today it leads the application of AI to industrial quality, with a team that keeps growing around that same idea.
Sergio Pesquere
CEO
A graduate in Industrial Electronics and Automation Engineering from the University of Cantabria, Sergio Pesquera Valadés leads digital transformation from an innovative and human perspective. As CEO and co-founder of Rely, he heads the company's strategy and growth, driving artificial intelligence solutions designed to redefine industrial efficiency. His focus is on freeing organisations from the day-to-day operational burden, enabling companies across sectors to reach their highest standards of quality and excellence.
Jaled Moustafá
CTO
As CTO and co-founder of Rely, Jaled Moustafa is the company's technological engine and the lead architect of its machine vision and deep learning solutions. With a solid engineering background and a mindset geared towards solving complex problems, Jaled leads the development of robust, integrable and scalable systems. His ability to turn artificial intelligence into agile and intuitive tools has been key to automating the most critical processes in today's industry.
Pilar Sánchez
BUSINESS DEVELOPER
As Business Development Director at Rely, Pilar Sánchez brings a strategic vision and strong commercial sensitivity to connect technological innovation with real market needs. Pilar stands out for her ability to turn complex challenges into opportunities for mutual growth, driving solid partnerships and high-impact projects. Her leadership is a key part of expanding the Rely ecosystem, helping organisations across different sectors remove day-to-day operational friction and focus on what truly creates value.
Pedro Casado
HEAD OF TECH
Pedro Casado has been a key figure in the company's journey since its beginnings. He currently leads the Rely product and project management, coordinating the direct relationship with customers. His hands-on approach and willingness to work on the factory floor ensure that every deployment fits the real industrial environment perfectly, making him the key bridge between Rely's technology and the day-to-day reality of production plants.
Abel González
HEAD OF AI
As Head of AI and Data Science at Rely, Abel brings a solid analytical foundation backed by his degree in Physics and his specialisation in Data Science. He is currently a PhD candidate in Computing, where he carries out research in artificial intelligence and advanced data analysis techniques. Abel leads the strategic development of AI algorithms and models that enable Siali to solve a wide range of challenges in the most demanding industrial environments. His scientific approach and experience in solving complex problems are key to turning the most advanced techniques into high-performance automated solutions.
Where we come from
We were born out of the uncertainty of two recent graduates. In 2018 we founded Siali Technologies in Cantabria without yet being clear about what the market really needed. Before that, in 2017, we had taken on Edimot, an educational robotics kit project that earned us the Yuzz Cantabria Award. But our course would soon shift towards the industrial paradigm.
We set up at the Technological Development Centre of the University of Cantabria (CDTUC), but from day one we knew that we wouldn't find what we were looking for there. Our goal was to work side by side with companies and get to know the sector from the inside, something that has always been essential for us: you don't learn the real needs from an office, only from where the work is done, where projects end up. It was in the factory that we found the need that would change everything: giving industrial cameras a "brain" through Deep Learning, so that machines could learn to detect flaws and errors in real time, without depending on human visual inspection.
That is how Rely was born. Not as a product dreamt up on a whiteboard, but as the answer to something we saw again and again on the plant floor: quality controls that depended on the human eye, tired after an eight-hour shift, or on rigid systems that had to be reprogrammed every time a part changed. We named the first product Inspector Calidad and tested it where we first found the need: automotive. Then came the timber sector.
2020 changed the scale of the project: we went from two sectors to also covering manufacturing and textiles, just as we won the EmprendedorXXI Award and joined the Forbes list of the 100 most creative Spaniards.
In 2022 we solved one of the most expensive bottlenecks in industrial AI: we built our own labelling tool. We stopped labelling data by hand and started doing it automatically, which multiplied the speed at which we brought new models into production.
The piece we are fitting into place now is VLMs, models that understand image and language at the same time. It is the leap that will allow us to take industrial quality inspection one step beyond where it is today.
Production has changed.
Inspection has too.
Rely adapts to your production line. To your needs. And to whatever comes next.
MOBA and traditional systems
Smart inspection with Rely
Investment
2020
2021
2022
2024
2026
How we work
What sets us apart is not a list of values, it's how we approach every project
· We do not look for the flashiest solution; we look for the one that works.
· Internally we summarise it as: we don't use a sledgehammer to crack a nut.
· Before taking on a project we conduct a feasibility study, and if we accept it, it is because we already know we will make it succeed.
98%
Integration success rate - Rely
20%
Industry average
We're still on the factory floor; we haven't left it. Every improvement we build into the product comes from something a customer told us with boots on the shop floor, not from an internal meeting. That's why Rely is not a closed development: it changes whenever the needs of the people using it change.
Nor do we chase AI trends; we see them coming beforehand. There are people on the team whose job is to keep track of what is published daily in the sector, and that is what led us to bet on machine vision when most were still using traditional systems. Now the same thing is happening with VLMs.
That 98% is no coincidence, it's the result of working this way.
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