Create sustainable value through AI & Machine Learning.
Many organisations don’t understand how to generate, measure, and maintain value from these capabilities, or continue to rely on black box data science solutions without reasoning behind predictions. Confidence globally in the ethics of using Machine Learning and AI both effectively and responsibly is decreasing, not increasing.
We enable clients with advanced capabilities within data science, ML, and AI, and help them confidently mobilise both concepts and advanced analytics ecosystems, at enterprise scale.
Maintain pace with AI and ML in the market, without the regret of managing constant change.
We believe in creating solutions that are sustainable for your organisation. We create success through our expertise and curiosity for enabling mature advanced analytics capabilities that can quickly enable new innovations.
Utilise machine learning on your data firehose to focus on what is actually important.
Automatically detect outliers within your data using ensemble machine learning models that can continually learn and adapt to new data.
Utilise segmentation and reinforcement learning techniques to better understand your customers and optimise behaviours such as click-throughs, up-sells, reactivation, and retention rates.
Data Ops and MLOps
Effectively operationalise and curate data & advanced analytics products.
See how we solved these challenges for our clients
Transforming market abuse and conduct surveillance for a global banking group.
We defined and implemented business operating model change and technology target state to increase effectiveness, efficiency and sustainability of the surveillance function.
How can the public sector use AI effectively? Part 1
In this two-part blog, we look at clearing up some of the myths surrounding AI and how the public sector could be using it to improve their working practices.
How can the public sector use AI effectively? Part 2
We take a pragmatic look at AI in the public sector and discuss the ethics surrounding it. Read part one.