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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Projects

HE Assistant

Horizon Europe projects analysis tool

Client

The problem

Every time Mosaic wants to draft a proposal for a Horizon Europe project, we need to find state-of-the-art technologies and projects in development in our area. Additionally, the task of finding candidates for the consortium is quite tedious. And even though all the information about projects, fundings and participants is publicly available, being able to make custom searches is not possible.

The solution

The purpose of the tool is to retain knowledge from a corpus of open documents from Horizon Europe projects.

It includes semantic search to answer questions about different aspects of the european projects.

Leveraging the growing popularity and technological advances in Generative Artificial Intelligence, the solution proposes using Large Language Models (LLMs) such as OpenAI’s ChatGPT, to transform natural language questions into customised queries for a data source.

Thanks to the logical capabilities of these models, complicated searches can be carried out automatically by being split up into more simple queries until all the necessary information is gathered.

    • The tool allows searching information on individual projects using natural language.
    • It includes filters to search for projects by metadata fields such as: total cost, start date, end date, duration, status, coordinator, etc.
    • The LLM creates the appropriate query and selects the information to be returned as output from each project.
    • Finally, it summarises the info into an answer in natural language.
    • The chat history between User and LLM is stored and passed as context at each request.
    • The conversation between LLMs is not stored.

Data

Through web scraping of data that can be found online at https://cordis.europa.eu/projects

Results

We have saved up to 25% of initial research time for the preparation tasks.

Do you have any questions?

We are always ready to help you and answer your questions. 





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