Artificial Intelligence (AI) is the simulation of human intelligence in machines such as computer systems to mimic the learning, problem-solving and decision-making capabilities of the human mind. At its core, AI requires a foundation of specialised hardware and software for training machine learning algorithms.
Through Alternative Data, Proprietary AI Models and Predict & Influence, SCL AI Business is more than equipped to help you achieve and maximise the desired end result.
A single holistic view of data first involves selecting data sources and obtaining access. Next, it would be essential to check the data's credibility, usefulness and readiness.
Big data discovery is done through a mash-up of relevant data sources or data sets. With quick analysis and visualisations, you can uncover various trends and patterns.
By incorporating relevant data into a model, you use machine learning to build and validate the predictive model developed.
Apply the predictive model onto data, and use behavioural science to drive and influence behaviours.
Find the best use of assets for your company. Strike a balance between efficiency and reliability.
By collecting millions of bytes of data from various sensors, a central monitoring system uses AI and machine learning to analyse and identify potential disruptions and bottlenecks in the production line. This greatly reduces the time and manpower required to monitor components individually, easing the workload for existing resources and enabling businesses to operate at paramount efficiency.
Achieving 100% Uptime
AI operates 24/7 without interruption and has no downtime. Compiling large amounts of data allows engineers to track all processes at a glance and therefore make faster and smarter decisions, giving rise to opportunities for preventive maintenance and reducing the chances of unplanned production downtime.
Reduction in Human Error
Computer systems are unlikely to make mistakes if programmed properly. With AI, decisions are taken and made from previously gathered information after applying certain algorithms. The reduction of human input also lowers the risk of firms facing setbacks due to human error. As a result, this will increase the probability of achieving accuracy with a greater degree of precision.