KADlytics' Net AI technology fuses multi-layer networks with Artificial Intelligence in order to elicit and learn about hidden structures within large dynamic datasets of complex systems.
Net AI can be employed in real-time creating an evolutionary multi-layer network that can be analysed independently and/or compared and contrasted with historical networks and structures within the networks themselves.
Net AI monitors and learns in real-time using the digital footprint (files) of a project or technical system. It hence leverages the wealth of existing data rather than requiring additional data collection. Net AI is a unique and patented technology that offers the power to:
Net AI is cloud-based, data-agnostic and system-independent. Designed to seamlessly integrate with your existing workflow, no changes to your data or existing infrastructure are required.
We start by hooking into your Enterprise Wide Systems such as, Shared Drives, Product Data Management and Business Process systems, and identify the objects of interest (nodes) and capture their attributes. For a Product Data Management system, the nodes are people, parts, assemblies and known dependencies are formed from the Created By, Owned By, Edited By and Part Of attributes. This forms our initial multi-layer network
Once created, we use our novel co-occurrence algorithms to identify potential hidden dependencies and reveal these to you. Working closely with our clients, we label these dependencies and train our AI to identify these across the multi-layer network providing a much richer and detailed description of your complex system.
With our multi-layer network formed, we apply our advanced network analysis techniques to detect features. We work closely with our clients to label these features in relation to their context (e.g. normal and abnormal behaviours) and train our AI to detect future occurrences. In addition, we can simulate changes to the network (e.g. someone leaving an organisation) and determine the effect of the change as well as events on the network (e.g. a change to a part) and subsequent propagation of changes that will be required.
We recognise the importance of integrating the results of our AI back into the business making sure the right people get the right information at the right time. To achieve this, we output to custom dashboards, provide information into existing dashboards, notifications, add-on apps and reporting. We work closely with our clients to deliver the results in the format that will best support their business needs.
Automated monitoring of who, what, where, when and why. Monitor effort, change, and contribution of people, teams, subcontractors, or suppliers over time, and examine the growth and evolution of systems and components.
Assess completeness against standards and RIBA stage-gates, monitor progression, monitor levels of file completeness, and identify what’s missing within and across file collections.
Real-time monitoring of the defined structural dependencies between objects and their evolution over time. Perform impact assessment, analyse collaborative working, and identify unconnected objects.
Identify and analyse emerging dependencies, and structural, functional, and organisational relationships. Reveal hidden patterns and form new insights, supporting agile resource planning, workflow management, and deep-dives into critical systems.
Gain insight via information dashboards, automatic report generation, and notifications integrated directly into your toolchain. We specialise in tailoring our analytics directly into your business processes and workflow.