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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Smart City Expo Barcelona

Our team participated in this year’s Smart City Expo World Congress, the leading global event for urban innovation. The expo brought together technology providers, municipalities, researchers, and institutions to explore how digital solutions can transform cities into smarter, safer, and more sustainable environments.

Mosaic Factor at Smart City World Expo Barcelona 2025 Mosaic Factor at Smart City World Expo Barcelona 2025

Here are the key trends and developments that stood out.

Digital Twins take center stage

Digital Twin (DT) technology was one of the most prominent themes across exhibitor stands. Cities are increasingly adopting DTs to simulate and manage complex urban systems. The most common applications showcased included:

  • Emergency and disaster management
  • Human behaviour modelling
  • Traffic and parking optimisation
  • Energy demand forecasting
  • Urban planning, such as identifying areas where new childcare facilities are needed

Several companies also presented the evolution of the Citiverse concept, part of a European initiative that integrates Digital Twins with cybersecurity, IoT, and other advanced technologies (European Commission Citiverse Project). Another highlight was the introduction of 4D Digital Twins, which incorporate the time dimension to enable predictive urban simulations (Nfold ROI).

Smart Cities and visual Language Models

AI innovation was another major focus. NVIDIA unveiled its Visual Language Model (VLM) platform for cities, designed to transform sensor-captured image data into an intelligent “city brain” capable of interpreting current and potential urban scenarios.

Practical applications were demonstrated in Leipzig, where AI-driven DTs are being used to optimise parking spaces and bicycle infrastructure. Meanwhile, the University of Hamburg showcased collaborative, open-source AI projects, emphasizing their interest in joining European-funded initiatives (DCS Intro 2024).

Cybersecurity and Global Engagement

Cybersecurity was a recurring theme throughout the expo, underscoring its critical role in safeguarding smart city infrastructures. Notably, the World Bank was actively involved, reflecting the global importance of secure digital ecosystems.

Our Contribution: Open Innovation Challenges

As part of our participation, we engaged in open innovation challenges, presenting proposals that leverage Large Language Models (LLMs) and Digital Twins for corporate applications. These initiatives demonstrate our commitment to pushing the boundaries of AI and urban technology, ensuring that cities of the future are not only smarter but also more resilient and inclusive.

Our presence at Smart City Expo Barcelona reaffirmed our role as a forward-looking technology provider. By contributing to discussions on Digital Twins, AI, cybersecurity, and open innovation, we continue to shape the future of urban living, driving solutions that make cities more adaptive, efficient, and human-centered.

Elena from Mosaic Factor at Smart City World Expo Barcelona