What Nimbus can provide?

Nimbus has a unique blend of software engineers, electronics engineers and academic researchers who work in various areas of Artificial Intelligence and Data Analytics. We have had many successful projects in AI domains such as:

Time Series Forecasting

Time series forecasting is an important area of machine learning that is often neglected. It is important because there are so many prediction problems that involve a time component. These problems are neglected because it is this time component that makes time series problems more difficult to handle.


Anomaly Detection

Anomaly detection is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data. Typically, anomalous data can be connected to some kind of problem or rare event such as e.g. bank fraud, medical problems, structural defects, malfunctioning equipment etc. We are able to pick out which data points can be considered anomalies, as identifying these events are typically very interesting from a business perspective.

Asset Scheduling

Proper scheduling is a critical foundation for any successful project/ operation. This is why automating the scheduling process from manual to fully automatic through an optimised scheduling algorithm can improve your organisation. By factoring in skill sets, location, and previous interactions, this automated scheduling software ensures faster response times, increased first time fix rates, and improved customer satisfaction. By utilising up-to-date GPS tracking and cloud-based computing, routes can be calculated instantly, tools and inventory tracked in real-time and complete visibility to technicians, managers, and the whole business operation.


Recommender Systems

A recommender system is a subclass of information filtering system that seeks to predict the "rating" or "preference" a user would give to an item. These systems can operate using a single input, like music, or multiple inputs within and across platforms like news, books, and search queries. There are also popular recommender systems for specific topics like restaurants and online dating. Recommender systems have been developed to explore research articles and experts, collaborators, financial services and life insurance.

Employee Testimonial

The work I do is varied and interesting. I have been able to work on AI applications for forecasting, anomaly detection, sentiment analysis in multiple domains. I also work on ‘traditional’ software development projects that have included web, desktop and microcontroller applications. What I like about the job is that the variety of projects ensures that every day provides fresh challenges. New projects often provide opportunities to use the most modern languages and frameworks, especially given that much of my team’s work involves creating new, innovative software and research using state-of-the-art technology.

The steep learning curve can seem almost overwhelming at times, but the work is stimulating and working conditions are very flexible. Working within the software team here has taught many lessons: how to plan projects, how to work both individually and in a team, how to conduct research, and how to manage client expectations. Not to mention the plethora of technical information about software development, deployment, Artificial Intelligence, etc.

Christian O'Leary
Software Developer

Data Analytics

How Nimbus Processes Big Data

Over forty researchers from Nimbus with over 160 industry partners, are working to ensure Ireland is at the heart of global data analytics research. Nimbus is committed to research that has a positive impact on society and are committed to protecting the rights of the citizen.

Nimbus offers data analytics solutions for a broad range of industry partners in ICT, healthcare, agriculture, finance, environmental and public services. Nimbus’s expertise includes the whole data value chain from the integration of multiple heterogeneous data sources, to discovering patterns and trends in data and making sense of them.

Innovative Solutions

These include using data to:

  • Develop products and services based on matching the short and long-term needs of individuals and organisations to a real time picture of information, opportunities, and services.
  • Understand customer behaviour to increase customer satisfaction, experience and loyalty.
  • Drive recommendations and support decision making.
  • Find optimal solutions to complex problems; and automate business processes.

Research Areas

  • Linked data
  • Semantic web
  • Machine learning and statistics
  • Media analytics
  • Personal sensing
  • Optimisation and decision analytics
  • Recommender systems

For more information on AI and Data Analytics please contact:

Dr. Conor Lynch