Data Enhanced Products

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Through different data sources (ie. physical tests) and ML models and usually in combination with our digital twin solutions, our data enhancement solution can learn, predict, and simulate outcomes to provide automatic product configurations that result in product and component improvement during the development process.

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Data As a Service Products

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Data as a Service (DaaS) is a cloud-based model that allows companies to access, manage, and analyse data on demand, without the need for extensive on-premise infrastructure.

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Optimisation Models

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Optimisation AI models allow our client to improve processes, reduce costs and increase competitiveness.

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Descriptive Models

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Descriptive models aim to describe patterns, relationships, and structures within data. They don’t predict future outcomes but provide insights into existing phenomena.

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Predictive Models

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Predictive modelling, also known as predictive analytics, is a discipline that uses statistical, mathematical and artificial intelligence techniques to predict future outcomes based on historical data.

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LLMs

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At Mosaic Factor, we focus on the creation of domain specific LLMs (or light Large Language Models) for our client organisations.

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Synthetic Data

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Synthetic data is artificial data generated from original data using a model trained to reproduce its characteristics and structure.

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Digital Twins

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To allow your business to monitor and optimise your assets in real-time Mosaic Factor uses Digital Twins. They can predict failures, detect inefficiencies, and improve decision-making through the use of data.

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Predictive Maintenance

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For Predictive maintenance models, we use historical and real-time data to anticipate equipment failures or maintenance needs. By analysing sensor data, maintenance logs, and other relevant information, we can schedule maintenance proactively, reduce downtime, and extend the lifespan of your machinery.

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Demand Cost Forecasting

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Our predictive models help businesses forecast demand for products or services. By analysing historical sales data, seasonality, economic factors, and external events we can optimise inventory levels, allocate resources efficiently, and minimise overstock or stockouts.

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Quality Analytics

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We identify patterns that correlate with defects or quality issues, allowing your business to take corrective actions early and maintain high-quality standards.

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Inventory Management

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We use predictive models to optimise inventory levels by considering factors such as lead time, demand variability, and storage costs.

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Supply Chain Management

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We can use historical and real-time data analytics to manage the supply chain, optimise transportation and ensure on-time product delivery.

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Market Understanding

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Our descriptive AI models provide valuable insights for decision-making and understanding complex systems of your organisation.

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Pattern Exploration

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Our descriptive AI models provide valuable insights for decision-making and understanding complex systems of your organisation.

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Trustworthy AI

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When using AI models in environments where compliance standards are important, Mosaic Factor can help your company be on top of data governance by applying trustworthy AI solutions.

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Logistics

Logistics

Mosaic Factor’s higher priority in Logistics is sharing key data across different Supply Chain players to optimise performance while managing sustainability by mitigating the impact of these operations.

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Automotive

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Mosaic Factor’s apply AI solutions in various aspects of the automotive industry, usually by enhancing vehicles and its components during its development.

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Mobility

Mobility

Mosaic Factor’s higher priority in Mobility is to optimise transport systems to people’s mobility while improving overall security and sustainability of transport solutions.

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Corporate Services

Corporate Services

Our machine learning and complex algorithms help organisations manage compliance and customer service to increase the service level of your organization while optimising resolution time for several processes.

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Manufacturing

Manufacturing

Mosaic Factor’s higher priority in Manufacturing is aid our clients decrease costs, increase sustainability while streamlining the production chain.

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Healthcare

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Mosaic Factor’s higher priority in Healthcare is making use of data to improve patient care and monitoring in a safe manner to optimise healthcare systems resources and assisting healthcare professionals.

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Mosaic Factor turns 10

Ten years ago, AI looked very different. Back in 2016, artificial intelligence was already powerful, but quieter. It lived mostly behind the scenes in predictive models, recommendation engines, and carefully engineered algorithms solving very specific problems. It was not something people talked about every day. It was not something everyone interacted with. That is the world Mosaic Factor was born into.

Today, AI is everywhere. It writes, creates, converses, and imagines. Terms like generative AI and large language models have entered everyday conversations, reshaping how we think about technology and its role in our lives.

As we celebrate our 10th anniversary, we are not just marking time. We are reflecting on how far AI has come and how we have grown alongside it.

The beginning

Mosaic Factor started with a simple but ambitious idea: to turn advanced AI into something practical, usable, and impactful.

Founded in 2016 by Stefano Persi (CEO) and José Fernandez (CTO), the company emerged from hands-on work in innovation projects. They saw an opportunity not just to build algorithms, but to help organisations truly use them.

In those early days, the focus was on “traditional AI“: predictive models, optimisation systems, and data‑driven decision tools. The challenge was not just accuracy. It was making these systems reliable, scalable, and understandable in real‑world environments. Which still is, to be fair.

From the very beginning, Mosaic Factor took a different approach: not just building AI, but building AI that is explainable and trustworthy.

A decade of change in AI

Over the past ten years, the field of AI has gone through a transformation few could have predicted:

  1. We have moved from structured data and classic machine learning to systems that can generate text, images, analysis, and ideas.
  2. From models that answered questions to models that hold conversations.
  3. From tools once used by specialists to platforms used by millions.
  4. The rise of generative AI and large language models has brought extraordinary possibilities, alongside new questions. How do we trust these systems? How do we use them responsibly?

Through all this, Mosaic Factor has remained present across both worlds. We have worked with traditional AI, where precision, interpretability, and robustness are essential. And we have embraced modern AI, where creativity, adaptability, and scale redefine what is possible.

One thing has never changed: our commitment to building AI that is explainable, trustworthy, and grounded in real impact. Because as AI becomes more powerful, trust matters more than ever.

The people behind the journey

At the heart of our 10‑year journey is something simple: people.

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The team at Mosaic Factor makes everything possible, bringing creativity, expertise, and passion to every project. Here are leadership reflections for this milestone:

CEO, Stefano Persi:

“When we started Mosaic Factor, our mission was clear: make AI truly work for people. Ten years later, I am proud that our purpose remains the same and that our team continues to push the boundaries of what responsible innovation looks like”.

CTO, José Fernandez:

“Technology evolves fast, but trust must move even faster. Our commitment to transparent, explainable AI has guided us from day one, and it will continue to shape how we build the next generation of intelligent systems”.

Chief Data Scientist, Burcu Kolbay:

“Over the past decade, data has become central to how we understand problems and make decisions. It’s been inspiring to see curiosity, data‑driven thinking, and advances in AI shape how we work every day. As these technologies evolve, our role is to guide them so intelligence serves people in meaningful and reliable ways and I’m excited for what comes next”.

Innovation Project Manager, Montserrat Anglès:

“Innovation is not just about embracing new technologies but about understanding how they can meaningfully transform the way organisations work. At Mosaic Factor, we have spent a decade turning cutting‑edge ideas into real‑world impact, and that spirit of experimentation and purpose continues to drive us forward”.

A special thank you goes to our team members and everyone who has contributed to our story. This milestone belongs to all of you. We are equally grateful to our clients, partners, and community who have supported us every step of the way. You have shaped who we are, and who we aspire to become.

Mosaic Factor team fun moments

Looking ahead

If the last decade has taught us anything, it is that change is constant, but purpose matters.
AI will continue to evolve, becoming faster, more capable, and more deeply embedded in everyday life. The challenge will not just be what we can build, but how we choose to build it.
At Mosaic Factor, our goal is clear:

  1. To design AI systems people can trust, understand, and rely on.
  2. To bridge innovation with responsibility.
  3. To grow into one of Europe’s leading AI and Big Data companies while staying true to the impact we want to create.

The story of AI is still being written. And we are proud to be part of it.