A statement said the Cyber Threat Platform collected security data across the network and used AI to create virtual replicas of real-world objects and users.
It then used predictive analysis to model expected behaviour and future state of objects and applied AI-powered reasoning to predict what any specific threat would end up doing.
If any threat was deemed to be a risk, then the company's Cyber Threat Intelligence Centre took action to quarantine or disable the threat before it could attack critical parts of the network.
“Actions as seemingly innocuous as accessing the server at an odd hour, or uploading an unusual file, can when placed in the correct context be a critical early indicator of malicious activity.
"This is the level at which we need to begin viewing threat detection, rather than responding reactively to an incident after it has occurred.”
The Platform is vendor-agnostic and can use data from a number of hardware and software companies.
“AI-driven predictive analytics is the logical next step for the cyber security industry. From here, the focus must be on modelling potential threats at the earliest possible stage to proactively minimise the potential harm,” Devaraj said.
“The local and international regulatory trend towards greater data transparency has raised the security stakes for companies which harbour sensitive information – particularly those in industries such as finance, education and healthcare – the latter of which has become a prized target for hackers.”