Identifying data-driven opportunities
Together we identify and clarify your data-driven opportunities to innovate and improve performance across sectors within your organisation.
What we do
Decision-making
We deliver impactful cutting-edge data, analytics and AI solutions to help you achieve desired outcomes and gain competitive advantages.
Enhancing data ecosystems
Understanding your data structure and knowing what data to prioritise to your organisational desired outcomes is key. Together we assess, analyse and build your essential data ecosystems.
Making the complex simple
We capture and visualise data in simple and intuitive ways. The tools we develop break down complexity and optimise operational decision making.
From unstructured data to insights
We refine, structure, aggregate and normalise vast amounts of data to help you establish the correct platform to become truly data-driven. By structuring the unstructured we are able to create true and reliable informational insights for better decision-making.
Data platforms
Our team of physicists, engineers, computer scientists, data scientists and researchers can work either within your existing infrastructure and visualisation platform, or help you establish new platforms. We work across a variery of platforms and tools delivered by Microsoft Azure, Amazon (AWS), Google Cloud, Tableau, Power BI, Qlik and many more.
Process
Thinking big - but starting small
- 1
We assess and identify - analyse and prioritise
With an analytical data-driven approach, and one of the strongest data, analytics and AI teams in Scandinavia we assess, identify, analyse and prioritise needs and desired outcomes.
- 2
We handle and prepare vast amounts of data
We relate data to business challenges and desired outcomes. We construct datasets from initial raw data and use both internal and external data.
- 3
We design and advance insights through models
Our team designs, builds and tests predictive models and algorithms, evaluates performance technically and tests effectiveness against business objectives.
- 4
We turn insights into actions
We create new insights and simplicity, thereby improving your decision-making process.
- 5
Adopt, enable, empower
We build capabilities to ensure that data-driven decision-making processes are successfully enacted upon across all stakeholder levels.
Learn more
Imagine if you could disrupt predictability
We believe that the coming decade will be all about using data better. This is where organisations will find their true competitive edge. We work across a variety of verticals and are here to help organisations unleash their maximum potential through data.
Meet our advisory board member
Dr. habil. Christian Igel
Our advisory board is a who's who of leaders and inspirers from within their fields, providing insight, guidance and best practices.
Dr. habil. Christian Igel is a professor in machine learning at DIKU and Director of SCIENCE AI Centre, University of Copenhagen. He is widely recognised for his knowledge within machine learning / artificial intelligence and has published a vast number of groundbreaking papers within the area of machine learning algorithms.
Christian Igel joined DIKU in 2010 and has been Director of Science AI Centre since 2018, which is set out to strengthen research and collaborations within artificial intelligence across the Faculty of Science and to manifest University of Copenhagen as a key player within artificial intelligence.
"I find the work of Halfspace very fascinating, and the team is very inspiring", Dr. habil Christian Igel
Meet our advisory board member
Prof. Pierre Pinson
Dr. Pierre Pinson is widely recognised within the fields of decision-making, forecasting, operations research and energy systems. Lately he has made significant contribution to e.g. peer-to-peer markets- and collaborative and market based analytics.
He has been a Professor at DTU since 2013, while he is the editor-in-chief of the International Journal of Forecasting (IJF). The IJF is the leading journal in the science and practice of predictive analytics, with the objectives to unify the field, to bridge the gap between theory and practice, and to eventually make forecasting useful and relevant for decision and policy makers.
"I often see companies with a vision, but they lack knowledge and expertise to execute on that. This is what I like with Halfspace. They can develop a vision, but are also do'ers. I see an agility in Halfspace that is rare and I think the value when working with data is to be agile. That you understand different settings and can relate to these", Prof. Pierre Pinson