Vrex

Vixel is the company behind Vrex, a real-time collaborative platform for capital (capex) projects across all industries — manufacturing, energy, infrastructure, healthcare, maritime and more. Vrex brings project data together so that decision-makers and stakeholders, not only technical specialists, can access and understand it, and reach better decisions faster.

Our core strength is data processing. First, we handle very large project data in line with industry standards, including models and reality-captured point clouds that other tools cannot open at scale. Second, in doing so we generate a unique new data source: a record of how decisions are actually made across thousands of collaborative reviews. The combination of standards-grade large-data handling and this proprietary decision-layer dataset is where we believe we lead the field, and it gives us a meaningful head start on the AI journey that every industry is now focused on.

We are looking for research and innovation partners interested in applying this capability to creative, AI-driven ways of working — improving efficiency, reducing rework and miscommunication, and supporting more sustainable outcomes across established industry activities.

Our value extends across the full circular asset lifecycle. The thousands of conversations and micro-decisions captured across collaborative reviews become a living operational record that translates into actionable insight during operations, and carries through major maintenance, decommissioning, reuse and material recovery. This holds across very different horizons: buildings and infrastructure that live 20+ years, where the decision history bridges generations of owners and operators; and manufacturing facilities, where major maintenance is frequent and the demolition and reconstruction of process lines is almost routine — making reusable, standards-based decision data a powerful enabler of circular, sustainable outcomes.

In a collaborative review, the project model itself becomes a kind of sensor: it reflects where a team's collective attention converges or scatters, which parts of the design are genuinely engaged with, and which questions are raised but never closed. We are turning that into precise, explainable risk signals — surfacing the weak signals that minutes and transcripts miss, early enough to act. The outcome we are after is simple: fewer surprises, less rework, and more sustainable, circular decisions across the whole asset lifecycle.