CADMATIC used its session to confront a problem many asset-heavy organisations quietly struggle with: the industry is drowning in data yet starved of clarity. Kari Mannor explained that information is scattered across engineering tools, maintenance systems, documents and operational platforms, creating an environment where the volume of data grows while trust and consistency diminish. CADMATIC aims to reverse this by linking these sources through a digital twin platform that acts as a unified frame of reference rather than an additional silo.
The presentation outlined how this platform draws from models, point clouds and intelligent objects to reflect the asset in a way that supports both project execution and decades of operational activity. Kari highlighted the reality that large organisations often maintain dozens of systems with incompatible tag structures and duplicated information; CADMATIC’s approach brings these together so that teams can navigate data more confidently and act with fewer uncertainties.
AI agents formed the other major theme. CADMATIC showcased practical use cases already delivering value, such as agents that update engineering libraries from trusted sources, reconcile conflicting tag conventions or assist with rule-based piping design. These tools remove repetitive work, strengthen data accuracy and let engineers focus on higher-value tasks. In CADMATIC’s view, digital twins supported by intelligent agents offer a pathway from today’s data chaos to a future defined by clarity, trustworthiness and better long-term asset decisions.
Speakers
