Trustworthy AI

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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Synthetic Data

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

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Descriptive Models

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

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

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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Digital Twins

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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Data Enhanced Products

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

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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Predictive Maintenance

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

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

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

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

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

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

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Pattern Exploration

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

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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

B:SM Tram Parquímetre

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

Healthcare

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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Augmented Intelligence Modelling Platform

We have new developments from the innovation project Green-log: we have delivered our Augmented Intelligence Modelling Platform (AIMP).

Our AIMP offers innovative tools for managing last-mile deliveries and planning multimodal fleet operations. We have integrated advanced modules for demand prediction, optimisation, and simulation.

In this project’s deliverable, we provide a comprehensive overview of the Augmented Intelligence Modelling Platform (AIMP), emphasizing its architecture, functionalities, and methodologies designed to address the challenges of urban logistics. We also outlined the platform’s development stages, key architectural components, dependencies, and user-facing functionalities, establishing a solid foundation for its continued refinement.

Significant progress has been made in the development of the AIMP, including the creation of a Minimum Viable Product (MVP) and subsequent iterative releases, implementation of a scalable architecture, and deployment of core functionalities such as demand prediction and quick optimization. These milestones highlight the platform’s ability to deliver practical and effective solutions for real-world urban logistics scenarios.

Moving forward, development efforts will focus on:

  • Expanding functionalities and ensuring compatibility across components.
  • Version 3 of the platform will introduce interactive features, allowing users to adjust optimization parameters directly within the application.
  • Version 4 will extend all functionalities to include all Living Labs, ensuring adaptability to diverse urban contexts.

The final version will incorporate the enhanced optimisation module, integrating simulation workflows to create a fully operational platform capable of addressing complex logistical needs.

Through continued iteration, stakeholder collaboration, and meticulous testing, the AIMP is on course to deliver a robust and adaptable solution for urban logistics, addressing the needs of Living Labs and showcasing its potential in real-world applications.

The simulation platform

Here you can have a sneak peak on how the AIMP looks like:

→ Check our Digital Twins solution