Pointcanvas is tackling one of the biggest challenges in infrastructure digitisation: turning complex 3D scans into accurate, usable engineering models. Founded by an engineer passionate about bridging the gap between physical assets and their digital representations, the company uses spatial AI to automatically classify and organise industrial environments, helping teams create higher-quality 3D models up to eight times faster. Supported by the Venture Builder Incubator (VBI) and the Bayes Centre, Pointcanvas has achieved significant milestones, including recognition as a top 40 Smart Building startup at BIM Munich 2025, the development of a state-of-the-art spatial AI model, and securing a £10,000 InnoConnect grant with the University of Edinburgh. As demand grows, the team is expanding its AI capabilities and infrastructure to help operators and surveyors streamline digital twin workflows across critical industries.

Can you tell us a little about your background and what inspired you to form a company?

I'm an engineer at heart, and I've always been fascinated by how we represent large physical structures in the digital domain. The more I talked with people in the industry, it surprised me how many critical assets still have no 3D model behind them. Scanning is part of the cost story, but the real bottleneck is the work of creating the geometry itself. Pointcanvas came out of wanting to close that gap for the industries that need it most.

What motivates you as an entrepreneur?  

What motivates me is seeing ideas turn into something tangible that people actually use. There's a particular satisfaction in working on critical infrastructure, the kind of assets that quietly keep industries running and knowing that better tools can make a real difference to the teams responsible for them. On top of that, the autonomy of building a company and the chance to talk with many like-minded individuals along the way is always engaging.

What is the problem you’re trying to solve?

In a simple sentence, Pointcanvas is digitising humanity's backbone infrastructure.

Critical infrastructure used in everyday life goes unnoticed by many, yet it forms the backbone of modern civilisation. Infrastructure across water, electricity, oil, gas and food processing all require key decisions throughout their lifetime and these are often made with a limited understanding of the full picture. We're aiming to remove that uncertainty by simplifying what is complex in 3D, focusing on the items that matter most and providing spatial insights to the operators who need them.

Describe your solution?

Pointcanvas AI automatically processes 3D scans of physical environments and turns them into labelled data that engineering teams can use directly in their existing design software. By doing the heavy lifting of identifying and organising what's in the scan, we accelerate modelling workflows by up to eight times and produce higher-fidelity 3D models, particularly in cluttered environments where manual processing typically struggles.

How has Venture Builder Incubator helped?

VBI has been instrumental in helping us define our target users and the most effective ways to reach them. The fireside chats and workshops are detailed, engaging and distil a lot of hard-won wisdom for founders. The Entrepreneur in Residence was a great help, giving us the chance to think through the problem and solution in real depth. The grant funding has been a meaningful boost as we continue to build out our solution. The guidance during the programme helped us shape a holistic proposal targeting the environments our clients use most for digital twin workflows, which gave Pointcanvas the foundation to put forward an InnoConnect proposal with clearly defined objectives and goals.

What were the benefits of the Bayes Centre?

Being part of Bayes gave us access to professional meeting rooms for client meetings, which proved useful in the early stages, as well as a dedicated space to meet in person as a team. Having a credible venue to host conversations made a real difference when engaging with prospective stakeholders.

What milestones have you achieved so far?

1.      We were selected as a top 40 Smart Building startup at BIM Munich 2025 during the VBI programme.

2.      We have trained a state-of-the-art spatial AI model for classifying objects in industrial scenes, allowing operators to automatically isolate areas of interest.

3.      We were awarded a £10k InnoConnect grant with the University of Edinburgh, which we are using to develop Autodesk plugins for industry.

What’s next on the horizon?  

Pointcanvas's base AI model to deliver even better results for our users. Interest from our website and direct enquiries has been steadily growing, with both operators and surveyors reaching out for help streamlining their workflows on their assets. On the infrastructure side, we're setting up our compute capacity to support more users and showcase the full range of our product offerings.

What advice would you offer to someone who's thinking about applying to VBI?

Definitely apply, don’t overthink it! The application process is simple and the experiences you will gain are worth it.
Find out more: Pointcanvas